U.S. patent application number 14/939013 was filed with the patent office on 2016-05-19 for monitoring treatment compliance using combined performance indicators.
This patent application is currently assigned to Elwha LLC. The applicant listed for this patent is Elwha LLC. Invention is credited to Jeffrey A. Bowers, Paul Duesterhoft, Daniel Hawkins, Roderick A. Hyde, Edward K.Y. Jung, Jordin T. Kare, Eric C. Leuthardt, Nathan P. Myhrvold, Michael A. Smith, Elizabeth A. Sweeney, Clarence T. Tegreene, Lowell L. Wood, JR., Victoria Y.H. Wood.
Application Number | 20160140986 14/939013 |
Document ID | / |
Family ID | 55962261 |
Filed Date | 2016-05-19 |
United States Patent
Application |
20160140986 |
Kind Code |
A1 |
Bowers; Jeffrey A. ; et
al. |
May 19, 2016 |
MONITORING TREATMENT COMPLIANCE USING COMBINED PERFORMANCE
INDICATORS
Abstract
Methods and systems for monitoring compliance of a patient with
a prescribed treatment regimen are described. Two or more patient
activities (including e.g., speech activity) are analyzed to
determine compliance with a treatment for a brain-related disorder.
Activity is detected unobtrusively during performance of routine
activities with activity sensor(s) at the patient location, patient
speech is detected during use of a communication system such as a
mobile telephone, and activity data is sent to a monitoring system
at a monitoring location. Activity and/or speech data is processed
at the patient location or monitoring location to identify activity
parameters or patterns that indicate whether the patient has
complied with the treatment regimen. Patient identity may be
determined through biometric identification or other authentication
techniques. The system may provide a report to an interested party,
for example a medical care provider or insurance company, regarding
patient compliance.
Inventors: |
Bowers; Jeffrey A.;
(Bellevue, WA) ; Duesterhoft; Paul; (Grapevine,
TX) ; Hawkins; Daniel; (Pleasanton, CA) ;
Hyde; Roderick A.; (Redmond, WA) ; Jung; Edward
K.Y.; (Bellevue, WA) ; Kare; Jordin T.; (San
Jose, CA) ; Leuthardt; Eric C.; (St. Louis, MO)
; Myhrvold; Nathan P.; (Medina, WA) ; Smith;
Michael A.; (Phoenix, AZ) ; Sweeney; Elizabeth
A.; (Seattle, WA) ; Tegreene; Clarence T.;
(Mercer Island, WA) ; Wood, JR.; Lowell L.;
(Bellevue, WA) ; Wood; Victoria Y.H.; (Livermore,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Elwha LLC |
Bellevue |
WA |
US |
|
|
Assignee: |
Elwha LLC
|
Family ID: |
55962261 |
Appl. No.: |
14/939013 |
Filed: |
November 12, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14543030 |
Nov 17, 2014 |
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14939013 |
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14543066 |
Nov 17, 2014 |
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14543030 |
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14729278 |
Jun 3, 2015 |
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14543066 |
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14729322 |
Jun 3, 2015 |
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14729278 |
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Current U.S.
Class: |
704/271 |
Current CPC
Class: |
G06F 19/3475 20130101;
A61B 5/4064 20130101; G16H 15/00 20180101; A61B 3/112 20130101;
A61B 3/113 20130101; A61B 5/4082 20130101; A61B 5/4833 20130101;
A61B 5/4088 20130101; A61B 5/4803 20130101; G10L 25/66 20130101;
A61B 5/165 20130101; A61B 5/163 20170801; G16H 20/70 20180101 |
International
Class: |
G10L 25/66 20060101
G10L025/66; G10L 17/00 20060101 G10L017/00; A61B 5/16 20060101
A61B005/16; A61B 5/0205 20060101 A61B005/0205; A61B 3/11 20060101
A61B003/11; A61B 3/113 20060101 A61B003/113; G06F 19/00 20060101
G06F019/00; A61B 5/00 20060101 A61B005/00 |
Claims
1. A system comprising: at least one receiving device for use at a
monitoring location for receiving at least one activity data signal
and at least one audio data signal from a communication system, the
at least one audio data signal including audio data representing
speech from a patient at a patient location sensed with at least
one audio sensor at the patient location during use of the
communication system and transmitted to the monitoring location,
the patient having a brain-related disorder and a prescribed
treatment regimen for treating at least one aspect of the
brain-related disorder, the at least one activity data signal
including activity data indicative of whether the patient has
complied with the prescribed treatment regimen, the activity data
representing at least one first activity of the patient; signal
processing circuitry configured to process the at least one
activity data signal to determine, based upon the at least one
first activity of the patient and at least one second activity of
the patient, whether the patient has complied with the prescribed
treatment regimen; and reporting circuitry configured to report a
conclusion based on the determination of whether the patient has
complied with the prescribed treatment regimen.
2.-4. (canceled)
5. The system of claim 1, including patient identification
circuitry configured to determine a presence of the patient from at
least one identity signal received by the at least one receiving
device at the monitoring location from the patient location;
wherein the signal processing circuitry is configured to identify
patient activity data corresponding to an activity of the patient
based at least in part on the determination of the presence of the
patient by the patient identification circuitry.
6. The system of claim 5, wherein the identity signal includes at
least a portion of the audio data signal, wherein the patient
identification circuitry includes speech analysis circuitry for
identifying at least a portion of the audio signal data that
resembles known speech of the patient, and wherein the signal
processing circuitry is configured to identify the patient activity
data by identifying activity data corresponding to a portion of the
audio signal that resembles known speech of the patient.
7.-24. (canceled)
25. The system of claim 1, wherein the at least one activity data
signal includes non-speech activity data, and wherein the signal
processing circuitry is configured to process the at least one
activity data signal to identify at least one non-speech activity
pattern that corresponds to unprompted performance of a non-speech
activity by the patient.
26. The system of claim 1, wherein the at least one activity data
signal includes non-speech activity data, and wherein the signal
processing circuitry includes an activity analyzer for analyzing
the activity data to determine a non-speech activity pattern; and a
comparator for comparing the non-speech activity pattern
represented by the activity data with the at least one
characteristic activity pattern.
27. (canceled)
28. The system of claim 1, wherein the activity data signal
includes audio data representing patient speech, and wherein the
signal processing circuitry includes a speech analyzer for
analyzing patient speech in the audio data signal to determine a
patient speech pattern.
29. The system of claim 28, wherein the signal processing circuitry
includes a comparator for comparing the patient speech pattern
determined from the audio data signal with at least one
characteristic speech pattern.
30.-37. (canceled)
38. The system of claim 1, wherein the at least one receiving
device is adapted to receive a physiological activity data signal
indicative of at least one physiological signal sensed from the
patient with at least one physiological sensor.
39.-44. (canceled)
45. The system of claim 1, including warning circuitry configured
deliver a warning to a threatened party in response to a
notification, the notification indicative of a determination that
the patient poses a threat based on the at least one first activity
and the at least one second activity; wherein the at least one
receiving device is configured to receive the notification from the
patient location.
46. A method of monitoring compliance of a patient with a treatment
regimen, comprising: receiving at least one audio data signal with
a receiving device at a monitoring location, the audio data signal
including audio data representing speech sensed from a patient at a
patient location during use of a communication system, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder;
receiving at least one activity data signal with the receiving
device, the activity data signal including activity data indicative
of whether the patient has complied with the treatment regimen, the
activity data representing at least one first activity of the
patient; determining with signal processing circuitry at the
monitoring location whether the patient has complied with the
treatment regimen, based upon the at least one first activity of
the patient and upon at least one second activity of the patient;
and reporting with reporting circuitry a conclusion based on the
determination of whether the patient has complied with the
prescribed treatment regimen.
47. The method of claim 46, including receiving with the at least
one receiving device a notification from the patient location, the
notification indicative of a determination of the patient posing a
threat based on the at least one first activity and the at least
one second activity; and delivering a warning to a threatened party
in response to the received notification.
48.-49. (canceled)
50. The method of claim 46, wherein the at least one first activity
of the patient and the at least one second activity of the patient
are non-verbal activities.
51. The method of claim 46, wherein receiving the at least one
activity data signal with the at least one receiving device
includes receiving an activity data signal representing the at
least one first activity of the patient, and wherein the audio data
signal represents the at least one second activity of the
patient.
52. (canceled)
53. The method of claim 46, wherein at least one of the at least
one first activity and at least one second activity of the patient
corresponds to performance of a non-speech activity.
54.-83. (canceled)
84. The method of claim 46, including receiving a signal indicative
of initiation of treatment of the patient according to the
treatment regimen and beginning to receive the at least one audio
data signal responsive to receipt of the signal indicative of
initiation of treatment of the patient.
85.-87. (canceled)
88. The method of claim 46, including determining a presence of the
patient with patient identification circuitry at the monitoring
location from at least one identity signal received at the
monitoring location from the patient location, and using the signal
processing circuitry to identify patient activity data
corresponding to activity of the patient based at least in part on
the determination of the presence of the patient by the patient
identification circuitry.
89.-107. (canceled)
108. The method of claim 46, wherein determining with signal
processing circuitry at the monitoring location whether the patient
has complied with the treatment regimen includes analyzing the at
least one activity data signal to determine at least one of a first
activity pattern from the at least one first activity signal and a
second activity pattern from the at least one second activity
signal; and comparing the at least one of the first activity
pattern and the second activity pattern signal with at least one
characteristic activity pattern.
109.-117. (canceled)
118. The method of claim 108, including comparing the at least one
of the first activity pattern and the second activity pattern with
a plurality of characteristic activity patterns.
119. The method of claim 118, including determining which of the
plurality of characteristic activity patterns best matches the at
least one of the first activity pattern and the second activity
pattern.
120.-121. (canceled)
122. The method of claim 46, wherein determining with signal
processing circuitry at the monitoring location whether the patient
has complied with the treatment regimen includes analyzing the at
least one activity data signal to determine a first activity
pattern from activity data corresponding to first activity;
analyzing the at least one activity data signal to determine a
second activity pattern activity corresponding to the second
activity; comparing the first activity pattern with at least one
first characteristic activity pattern; and comparing the second
activity pattern with at least one second characteristic activity
pattern.
123.-143. (canceled)
144. A computer program product comprising: a non-transitory
signal-bearing medium bearing: one or more instructions for
controlling the receiving of at least one audio data signal with a
receiving device at a monitoring location, the audio data signal
including audio data representing speech sensed from a patient at a
patient location during use of a communication system, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder; one
or more instructions for controlling the receiving of at least one
activity data signal with the receiving device, the activity data
signal including activity data indicative of whether the patient
has complied with the treatment regimen, the activity data
representing at least one first activity of the patient; one or
more instructions for determining whether the patient has complied
with the treatment regimen, based upon the at least one first
activity of the patient and upon at least one second activity of
the patient; and one or more instructions for controlling reporting
circuitry to report a conclusion based on the determination of
whether the patient has complied with the prescribed treatment
regimen.
145.-174. (canceled)
175. The system of claim 5, wherein the identity signal includes at
least one of an image signal received from an imaging device at the
patient location, a biometric signal from at least one biometric
sensor at the patient location, an authentication factor, a
security token, a password, a digital signature, a cryptographic
key, a cell phone identification code, an electronic serial number,
a mobile identification number, a system identification code, and
an RFID signal.
176. The system of claim 1, including at least one of an input
device for receiving prescription information indicative of the
prescribed treatment regimen and a data storage device for storing
prescription information indicative of the prescribed treatment
regimen.
177. The system of claim 1, including timing circuitry configured
to control timing of operation of at least a portion of the system
to perform substantially continuously, intermittently, or according
to a schedule, at least one of receiving the at least one activity
data signal with the at least one receiving device, receiving the
at least one audio data signal with the at least one receiving
device, processing the at least one activity data signal with the
signal processing circuitry, and reporting the conclusion with the
reporting circuitry.
178. The system of claim 1, wherein the reporting circuitry
includes at least one of a display device, circuitry for generating
an email notification, circuitry for transmitting a notification to
a wireless device, circuitry for generating an audio alarm, and
circuitry for storing a notification in a data storage device.
179. The method of claim 53, wherein at least one of the at least
one first activity and at least one second activity of the patient
is an eye movement activity, a motor activity, typing, providing
input via a user interface device, walking, an activity of daily
life, performing a hygiene activity, washing, eating, dressing,
brushing hair, brushing hair, combing hair, preparing food,
interacting with another person, interacting with an animal,
interacting with a machine, interacting with an electronic device,
or using an implement.
180. The method of claim 46, wherein the activity data signal
contains activity data indicative of at least one of a keystroke
pattern, an activity performance pattern, an activity performance
rate, an activity performance time, an activity performance
frequency, an activity performance variability, an activity
performance accuracy, an activity performance error rate.
181. The method of claim 46, wherein the activity data signal
contains activity data including data from at least one of a
pressure sensor, a force sensor, a capacitive sensor, an imaging
device, a motion sensor, a motion capture device, an acceleration
sensor, and an optical sensor.
182. The method of claim 46, including receiving with the receiving
device at least one physiological activity data signal indicative
of at least one physiological signal sensed from the patient with
at least one physiological sensor, wherein the at least one
physiological activity data signal includes at least one of data
indicative of whether the patient has complied with the treatment
regimen, EEG data, event-related potential data, heart rate data,
eye position data, and pupil diameter data.
183. The method of claim 46, including performing at least one of
receiving the at least one audio data signal, receiving the at
least one activity data signal, determining with the signal
processing circuitry, and reporting the conclusion substantially
continuously, intermittently, or according to a schedule.
184. The method of claim 88, wherein the identity signal includes
at least one of at least a portion of the activity data signal and
at least a portion of the audio data signal.
185. The method of claim 88, wherein the identity signal includes
an image signal received from an imaging device at the patient
location, and wherein determining the presence of the patient with
the patient identification circuitry at the monitoring location
from the at least one identity signal includes analyzing the image
signal to determine the presence of the patient through at least
one of facial recognition, gait recognition, or posture
recognition.
186. The method of claim 88, wherein the identity signal includes
at least one of an image signal received from an imaging device at
the patient location and a biometric signal from at least one
biometric sensor at the patient location.
187. The method of claim 88, wherein the identity signal includes
at least one of an authentication factor, a security token, a
password, a digital signature, a cryptographic key, a cell phone
identification code, an electronic serial number, a mobile
identification number, a system identification code, and an RFID
signal.
188. The method of claim 46, including at least one of storing
prescription information in a data storage device at the monitoring
location, the prescription information indicative of the prescribed
treatment regimen; receiving prescription information indicative of
the prescribed treatment regimen; and prescribing the treatment
regimen intended to treat the at least one aspect of the
brain-related disorder to the patient.
189. The method of claim 46, wherein receiving the at least one
activity data signal includes at least one of receiving a wireless
signal, receiving data via a computer network connection, receiving
data via a communication port, and receiving data via a data
storage device.
190. The method of claim 108, wherein the at least one
characteristic activity pattern includes at least one previous
activity pattern of the patient or at least one population activity
pattern representative of a typical activity pattern of a
population of subjects.
191. The method of claim 108, wherein the at least one
characteristic activity pattern includes at least one previous
activity pattern of the patient, wherein the at least one previous
activity pattern is representative of an activity pattern of the
patient prior to initiation of treatment of the brain-related
disorder, an activity pattern of the patient after initiation of
treatment of the brain-related disorder, an activity pattern of the
patient during known compliance of the patient with a treatment of
the brain-related disorder, or an activity pattern of the patient
during treatment at a specified treatment regimen.
192. The method of claim 108, wherein the at least one
characteristic activity pattern includes at least one population
activity pattern representative of a typical activity pattern of a
population of subjects selected from a population without the
brain-related disorder, an untreated population with the
brain-related disorder, and a population having the brain-related
disorder stabilized by a treatment regimen.
193. The method of claim 119, including determining a treatment
regimen corresponding to the characteristic activity pattern that
best matches the at least one of the first activity pattern and the
second activity pattern, wherein the plurality of characteristic
activity patterns include a plurality of previous activity patterns
each representative of an activity pattern of the patient
undergoing a different treatment regimen for treatment of the
brain-related disorder or a plurality of population activity
patterns each representative of a typical activity pattern for a
population of subjects undergoing a different treatment regimen for
treatment of the brain-related disorder.
194. The method of claim 46, wherein reporting a conclusion based
on the determination of whether the patient has complied with the
prescribed treatment regimen includes at least one of displaying a
report on a display device, generating an email notification,
transmitting a notification to a wireless device, generating an
audio alarm, and storing a notification in a data storage
device.
195. The method of claim 46, wherein determining, based upon the
activity data signal, whether the patient has complied with the
prescribed treatment regimen includes at least one of determining
that the patient has failed to comply with the prescribed treatment
regimen, determining that the patient has complied with the
prescribed treatment regimen, and determining a degree of
compliance of the patient with the prescribed treatment
regimen.
196. The method of claim 46, wherein the brain-related disorder
includes at least one of an emotional disorder, a personality
disorder, a mental disorder, a traumatic brain-injury-related
disorder, schizophrenia, Parkinson's disease, an Autism Spectrum
Disorder, Alzheimer's disease, Bipolar Disorder, depression, a
psychological disorder, and a psychiatric disorder.
Description
[0001] If an Application Data Sheet (ADS) has been filed on the
filing date of this application, it is incorporated by reference
herein. Any applications claimed on the ADS for priority under 35
U.S.C. .sctn..sctn.119, 120, 121, or 365(c), and any and all
parent, grandparent, great-grandparent, etc. applications of such
applications, are also incorporated by reference, including any
priority claims made in those applications and any material
incorporated by reference, to the extent such subject matter is not
inconsistent herewith.
CROSS-REFERENCE TO RELATED APPLICATIONS
[0002] The present application claims the benefit of the earliest
available effective filing date(s) from the following listed
application(s) (the "Priority Applications"), if any, listed below
(e.g., claims earliest available priority dates for other than
provisional patent applications or claims benefits under 35 USC
.sctn.119(e) for provisional patent applications, for any and all
parent, grandparent, great-grandparent, etc. applications of the
Priority Application(s)).
PRIORITY APPLICATIONS
[0003] The present application constitutes a continuation-in-part
of U.S. patent application Ser. No. 14/543,030, entitled MONITORING
TREATMENT COMPLIANCE USING SPEECH PATTERNS PASSIVELY CAPTURED FROM
A PATIENT ENVIRONMENT, naming Jeffrey A. Bowers, Paul Duesterhoft,
Daniel Hawkins, Roderick A. Hyde, Edward K. Y. Jung, Jordin T.
Kare, Eric C. Leuthardt, Nathan P. Myhrvold, Michael A. Smith,
Elizabeth A. Sweeney, Clarence T. Tegreene, and Lowell L. Wood, Jr.
as inventors, filed Nov. 17, 2014 with attorney docket no.
0810-004-006-000000, which is currently co-pending or is an
application of which a currently co-pending application is entitled
to the benefit of the filing date.
[0004] The present application constitutes a continuation-in-part
of U.S. patent application Ser. No. 14/543,066, entitled
DETERMINING TREATMENT COMPLIANCE USING SPEECH PATTERNS PASSIVELY
CAPTURED FROM A PATIENT ENVIRONMENT, naming Jeffrey A. Bowers, Paul
Duesterhoft, Daniel Hawkins, Roderick A. Hyde, Edward K. Y. Jung,
Jordin T. Kare, Eric C. Leuthardt, Nathan P. Myhrvold, Michael A.
Smith, Elizabeth A. Sweeney, Clarence T. Tegreene, and Lowell L.
Wood, Jr. as inventors, filed 17 Nov. 2014 with attorney docket no.
0810-004-007-000000, which is currently co-pending or is an
application of which a currently co-pending application is entitled
to the benefit of the filing date.
[0005] The present application constitutes a continuation-in-part
of U.S. patent application Ser. No. 14/729,278, entitled MONITORING
TREATMENT COMPLIANCE USING SPEECH PATTERNS CAPTURED DURING USE OF A
COMMUNICATION SYSTEM, naming Jeffrey A. Bowers, Paul Duesterhoft,
Daniel Hawkins, Roderick A. Hyde, Edward K. Y. Jung, Jordin T.
Kare, Eric C. Leuthardt, Nathan P. Myhrvold, Michael A. Smith,
Elizabeth A. Sweeney, Clarence T. Tegreene, and Lowell L. Wood, Jr.
as inventors, filed Jun. 3, 2015 with attorney docket no.
0810-004-008-000000, which is currently co-pending or is an
application of which a currently co-pending application is entitled
to the benefit of the filing date.
[0006] The present application constitutes a continuation-in-part
of U.S. patent application Ser. No. 14/729,322, entitled
DETERMINING TREATMENT COMPLIANCE USING SPEECH PATTERNS CAPTURED
DURING USE OF A COMMUNICATION SYSTEM, naming Jeffrey A. Bowers,
Paul Duesterhoft, Daniel Hawkins, Roderick A. Hyde, Edward K. Y.
Jung, Jordin T. Kare, Eric C. Leuthardt, Nathan P. Myhrvold,
Michael A. Smith, Elizabeth A. Sweeney, Clarence T. Tegreene, and
Lowell L. Wood, Jr. as inventors, filed Jun. 3, 2015 with attorney
docket no. 0810-004-009-000000, which is currently co-pending or is
an application of which a currently co-pending application is
entitled to the benefit of the filing date.
[0007] If the listings of applications provided above are
inconsistent with the listings provided via an ADS, it is the
intent of the Applicant to claim priority to each application that
appears in the Domestic Benefit/National Stage Information section
of the ADS and to each application that appears in the Priority
Applications section of this application.
[0008] All subject matter of the Priority Applications and of any
and all applications related to the Priority Applications by
priority claims (directly or indirectly), including any priority
claims made and subject matter incorporated by reference therein as
of the filing date of the instant application, is incorporated
herein by reference to the extent such subject matter is not
inconsistent herewith.
SUMMARY
[0009] In an aspect, a system includes, but is not limited to, at
least one receiving device for use at a monitoring location for
receiving an activity data signal transmitted to the monitoring
location from a patient location, the activity data signal
containing activity data representing at least one non-speech
activity pattern in activity sensed from a patient with at least
one activity sensor in an unobtrusive activity-detection system at
the patient location during performance of the non-speech activity
by the patient, the patient having a brain-related disorder and a
prescribed treatment regimen for treating at least one aspect of
the brain-related disorder, signal processing circuitry configured
to analyze the activity data signal to determine whether the
activity data represents at least one non-speech activity pattern
that matches at least one characteristic activity pattern,
compliance determination circuitry configured to determine whether
the patient has complied with the prescribed treatment regimen
based upon whether the activity data represents the non-speech
activity pattern that matches the at least one characteristic
activity pattern, and reporting circuitry configured to report a
conclusion based on the determination of whether the patient has
complied with the prescribed treatment regimen. In addition to the
foregoing, other system aspects are described in the claims,
drawings, and text forming a part of the disclosure set forth
herein.
[0010] In an aspect, a method of monitoring compliance of a patient
with a prescribed treatment regimen includes, but is not limited
to, receiving an activity data signal with a receiving device at a
monitoring location, the activity data signal transmitted to the
monitoring location from a patient location, the activity data
signal containing activity data representing at least one
non-speech activity pattern in activity sensed from a patient with
at least one activity sensor in an unobtrusive activity-detection
system at the patient location during performance of the non-speech
activity by the patient, the patient having a brain-related
disorder and a prescribed treatment regimen intended to treat at
least one aspect of the brain-related disorder, analyzing the
activity data signal with signal processing circuitry at the
monitoring location to determine whether the activity data
represents at least one non-speech activity pattern that matches at
least one characteristic activity pattern, determining with
compliance determination circuitry at the monitoring location
whether the patient has complied with the prescribed treatment
regimen based on whether the activity data represents the at least
one non-speech activity pattern that matches the at least one
characteristic activity pattern, and reporting with reporting
circuitry a conclusion based on the determination of whether the
patient has complied with the prescribed treatment regimen. In
addition to the foregoing, other method aspects are described in
the claims, drawings, and text forming a part of the disclosure set
forth herein.
[0011] In an aspect, a computer program product includes, but is
not limited to, a non-transitory signal-bearing medium bearing one
or more instructions for receiving an activity data signal with a
receiving device at a monitoring location, the activity data signal
transmitted to the monitoring location from a patient location, the
activity data signal containing activity data representing at least
one non-speech activity pattern in activity sensed from a patient
with at least one activity sensor in an unobtrusive
activity-detection system at the patient location during
performance of the non-speech activity by the patient, the patient
having a brain-related disorder and a prescribed treatment regimen
intended to treat at least one aspect of the brain-related
disorder, one or more instructions for analyzing the activity data
signal with signal processing circuitry at the monitoring location
to determine whether the activity data represents at least one
non-speech activity pattern that matches at least one
characteristic activity pattern, one or more instructions for
determining with compliance determination circuitry at the
monitoring location whether the patient has complied with the
prescribed treatment regimen based on whether the activity data
represents the at least one non-speech activity pattern that
matches the at least one characteristic activity pattern, and one
or more instructions for reporting with reporting circuitry a
conclusion based on the determination of whether the patient has
complied with the prescribed treatment regimen. In addition to the
foregoing, other aspects of a computer program product including
one or more non-transitory machine-readable data storage media
bearing one or more instructions are described in the claims,
drawings, and text forming a part of the disclosure set forth
herein.
[0012] In an aspect, a system includes, but is not limited to a
computing device, and instructions that when executed on the
computing device cause the computing device to control the
receiving of an activity data signal with a receiving device at a
monitoring location, the activity data signal transmitted to the
monitoring location from a patient location, the activity data
signal containing activity data representing at least one
non-speech activity pattern in activity sensed from a patient with
at least one activity sensor in an unobtrusive activity-detection
system at the patient location during performance of the non-speech
activity by the patient, the patient having a brain-related
disorder and a prescribed treatment regimen intended to treat at
least one aspect of the brain-related disorder, analyze the
activity data signal with signal processing circuitry at the
monitoring location to determine whether the activity data
represents at least one non-speech activity pattern that matches at
least one characteristic activity pattern, determine with
compliance determination circuitry at the monitoring location
whether the patient has complied with the prescribed treatment
regimen based on whether the activity data represents the at least
one non-speech activity pattern that matches the at least one
characteristic activity pattern, and control the reporting with
reporting circuitry of a conclusion based on the determination of
whether the patient has complied with the prescribed treatment
regimen. In addition to the foregoing, other system aspects are
described in the claims, drawings, and text forming a part of the
disclosure set forth herein.
[0013] In an aspect, an unobtrusive activity-detection system
includes, but is not limited to, at least one activity sensor for
sensing at least one activity signal including a non-speech
activity pattern corresponding to performance of a non-speech
activity by a patient at a patient location, the patient having a
brain-related disorder and a prescribed treatment regimen for
treating at least one aspect of the brain-related disorder,
activity detection circuitry configured to identify at least one
section of the at least one activity signal containing the
non-speech activity pattern, activity analysis circuitry for
processing the at least one section of the at least one activity
signal to generate activity data including data indicative of
whether the patient has complied with the treatment regimen, and at
least one transmitting device for transmitting an activity data
signal including the activity data including data indicative of
whether the patient has complied with the treatment regimen from
the patient location to a receiving device at a monitoring
location. In addition to the foregoing, other system aspects are
described in the claims, drawings, and text forming a part of the
disclosure set forth herein.
[0014] In an aspect, a method includes, but is not limited to,
sensing with at least one activity sensor in an unobtrusive
activity-detection system at least one activity signal including a
non-speech activity pattern corresponding to performance of a
non-speech activity by a patient at a patient location, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder,
processing the at least one activity signal with activity detection
circuitry in the unobtrusive activity-detection system to identify
at least one section of the at least one activity signal containing
the non-speech activity pattern, analyzing the at least one section
of the at least one activity signal with activity analysis
circuitry in the unobtrusive activity-detection system to generate
activity data including data indicative of whether the patient has
complied with the treatment regimen, and transmitting an activity
data signal including the activity data including data indicative
of whether the patient has complied with the treatment regimen to a
receiving device at a monitoring location with at least one
transmitting device at the patient location. In addition to the
foregoing, other method aspects are described in the claims,
drawings, and text forming a part of the disclosure set forth
herein.
[0015] In an aspect, a computer program product includes, but is
not limited to, a non-transitory signal-bearing medium bearing one
or more instructions for sensing with at least one activity sensor
in an unobtrusive activity-detection system at least one activity
signal including a non-speech activity pattern corresponding to
performance of a non-speech activity by a patient at a patient
location, the patient having a brain-related disorder and a
prescribed treatment regimen for treating at least one aspect of
the brain-related disorder, one or more instructions for processing
the at least one activity signal with activity detection circuitry
in the unobtrusive activity-detection system to identify at least
one section of the at least one activity signal containing the
non-speech activity pattern, one or more instructions for analyzing
the at least one section of the at least one activity signal with
activity analysis circuitry in the unobtrusive activity-detection
system to generate activity data including data indicative of
whether the patient has complied with the treatment regimen, and
one or more instructions for transmitting an activity data signal
including the activity data including data indicative of whether
the patient has complied with the treatment regimen to a receiving
device at a monitoring location with at least one transmitting
device at the patient location. In addition to the foregoing, other
aspects of a computer program product including one or more
non-transitory machine-readable data storage media bearing one or
more instructions are described in the claims, drawings, and text
forming a part of the disclosure set forth herein.
[0016] In an aspect, a system includes, but is not limited to, a
computing device and instructions that when executed on the
computing device cause the computing device to control the sensing
with at least one activity sensor in an unobtrusive
activity-detection system of at least one activity signal including
a non-speech activity pattern corresponding to performance of a
non-speech activity by a patient at a patient location, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder,
process the at least one activity signal with activity detection
circuitry in the unobtrusive activity-detection system to identify
at least one section of the at least one activity signal containing
the non-speech activity pattern, analyze the at least one section
of the at least one activity signal with activity analysis
circuitry in the unobtrusive activity-detection system to generate
activity data including data indicative of whether the patient has
complied with the treatment regimen, and control the transmitting
of an activity data signal including the activity data including
data indicative of whether the patient has complied with the
treatment regimen to a receiving device at a monitoring location
with at least one transmitting device at the patient location. In
addition to the foregoing, other system aspects are described in
the claims, drawings, and text forming a part of the disclosure set
forth herein.
[0017] In an aspect, a system includes, but is not limited to, at
least one receiving device for use at a monitoring location for
receiving at least one activity data signal and at least one audio
data signal from a communication system, the at least one audio
data signal including audio data representing speech from a patient
at a patient location sensed with at least one audio sensor at the
patient location during use of the communication system and
transmitted to the monitoring location, the patient having a
brain-related disorder and a prescribed treatment regimen for
treating at least one aspect of the brain-related disorder, the at
least one activity data signal including activity data indicative
of whether the patient has complied with the prescribed treatment
regimen, the activity data representing at least one first activity
of the patient, signal processing circuitry configured to process
the at least one activity data signal to determine based upon the
at least one first activity of the patient and at least one second
activity of the patient whether the patient has complied with the
prescribed treatment regimen, and reporting circuitry configured to
report a conclusion based on the determination of whether the
patient has complied with the prescribed treatment regimen. In
addition to the foregoing, other system aspects are described in
the claims, drawings, and text forming a part of the disclosure set
forth herein.
[0018] In an aspect, a method of monitoring compliance of a patient
with a treatment regimen includes, but is not limited to receiving
at least one audio data signal with a receiving device at a
monitoring location, the audio data signal including audio data
representing speech sensed from a patient at a patient location
during use of a communication system, the patient having a
brain-related disorder and a prescribed treatment regimen for
treating at least one aspect of the brain-related disorder,
receiving at least one activity data signal with the receiving
device, the activity data signal including activity data indicative
of whether the patient has complied with the treatment regimen, the
activity data representing at least one first activity of the
patient, determining with signal processing circuitry at the
monitoring location whether the patient has complied with the
treatment regimen, based upon the at least one first activity of
the patient and upon at least one second activity of the patient,
and reporting with reporting circuitry a conclusion based on the
determination of whether the patient has complied with the
prescribed treatment regimen. In addition to the foregoing, other
method aspects are described in the claims, drawings, and text
forming a part of the disclosure set forth herein.
[0019] In an aspect, a computer program product includes, but is
not limited to, a non-transitory signal-bearing medium bearing one
or more instructions for controlling the receiving of at least one
audio data signal with a receiving device at a monitoring location,
the audio data signal including audio data representing speech
sensed from a patient at a patient location during use of a
communication system, the patient having a brain-related disorder
and a prescribed treatment regimen for treating at least one aspect
of the brain-related disorder, one or more instructions for
controlling the receiving of at least one activity data signal with
the receiving device, the activity data signal including activity
data indicative of whether the patient has complied with the
treatment regimen, the activity data representing at least one
first activity of the patient, one or more instructions for
determining whether the patient has complied with the treatment
regimen, based upon the at least one first activity of the patient
and upon at least one second activity of the patient, and one or
more instructions for controlling reporting circuitry to report a
conclusion based on the determination of whether the patient has
complied with the prescribed treatment regimen. In addition to the
foregoing, other aspects of a computer program product including
one or more non-transitory machine-readable data storage media
bearing one or more instructions are described in the claims,
drawings, and text forming a part of the disclosure set forth
herein.
[0020] In an aspect, a system includes, but is not limited to, a
computing device, and instructions that when executed on the
computing device cause the computing device to control the
receiving of at least one audio data signal with a receiving device
at a monitoring location, the audio data signal including audio
data representing speech sensed from a patient at a patient
location during use of a communication system, the patient having a
brain-related disorder and a prescribed treatment regimen for
treating at least one aspect of the brain-related disorder, control
the receiving of at least one activity data signal with the
receiving device, the activity data signal including activity data
indicative of whether the patient has complied with the treatment
regimen, the activity data representing at least one first activity
of the patient, determining whether the patient has complied with
the treatment regimen, based upon the at least one first activity
of the patient and upon at least one second activity of the
patient, and controlling reporting circuitry to report a conclusion
based on the determination of whether the patient has complied with
the prescribed treatment regimen. In addition to the foregoing,
other system aspects are described in the claims, drawings, and
text forming a part of the disclosure set forth herein.
[0021] In an aspect, a system includes, but is not limited to, at
least one audio sensor in a communication system for sensing at
least one audio signal including patient speech from a patient at a
patient location during use of the communication system, the
patient having a brain-related disorder and a prescribed treatment
regimen for treating at least one aspect of the brain-related
disorder, at least one first activity sensor for sensing at least
one first activity signal indicative of a first activity of the
patient, signal processing circuitry configured to process the at
least one first activity signal and at least one second activity
signal indicative of a second activity of the patient to generate
at least one activity data signal, the activity data signal
containing activity data indicative of whether the patient has
complied with the treatment regimen, and at least one transmitting
device at the patient location for transmitting the at least one
activity data signal and at least one audio data signal based on
the at least one audio signal to a receiving device at a monitoring
location. In addition to the foregoing, other system aspects are
described in the claims, drawings, and text forming a part of the
disclosure set forth herein.
[0022] In an aspect, a method includes, but is not limited to,
sensing with at least one audio sensor in a communication system at
least one audio signal including patient speech from a patient at a
patient location during use of the communication system, the
patient having a brain-related disorder and a prescribed treatment
regimen for treating at least one aspect of the brain-related
disorder, sensing with at least one first activity sensor in the
communication system at least one first activity signal indicative
of a first activity of the patient, processing with signal
processing circuitry the at least one first activity signal and at
least one second activity signal indicative of a second activity of
the patient to generate at least one activity data signal, the
activity data signal containing data indicative of whether the
patient has complied with the treatment regimen, and transmitting
the at least one activity data signal and at least one audio data
signal based on the at least one audio signal to a receiving device
at a monitoring location with a transmitting device at the patient
location. In addition to the foregoing, other method aspects are
described in the claims, drawings, and text forming a part of the
disclosure set forth herein.
[0023] In an aspect, a system includes, but is not limited to, a
computing device and instructions that when executed on the
computing device cause the computing device to control sensing with
at least one audio sensor of at least one audio signal including
patient speech from a patient at a patient location, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder,
control sensing with at least one first activity sensor in an
unobtrusive activity-detection system of at least one first
activity signal indicative of a first activity of the patient,
process with signal processing circuitry the at least one first
activity signal and at least one second activity signal indicative
of a second activity of the patient to generate at least one
activity data signal, the activity data signal containing data
indicative of whether the patient has complied with the treatment
regimen, and control transmitting with a transmitting device at the
patient location of the at least one activity data signal and at
least one audio data signal based on the at least one audio signal
to a receiving device at a monitoring location. In addition to the
foregoing, other system aspects are described in the claims,
drawings, and text forming a part of the disclosure set forth
herein.
[0024] In an aspect, a computer program product includes, but is
not limited to a non-transitory signal-bearing medium bearing one
or more instructions for controlling sensing of at least one audio
signal including patient speech from a patient at a patient
location, the patient having a brain-related disorder and a
prescribed treatment regimen for treating at least one aspect of
the brain-related disorder, one or more instructions for
controlling sensing with at least one first activity sensor in an
unobtrusive activity-detection system of at least one first
activity signal indicative of a first activity of the patient, one
or more instructions for processing with signal processing
circuitry the at least one first activity signal and at least one
second activity signal indicative of a second activity of the
patient to generate at least one activity data signal, the activity
data signal containing data indicative of whether the patient has
complied with the treatment regimen, and one or more instructions
for controlling transmitting with a transmitting device at the
patient location of the at least one activity data signal and at
least one audio data signal based on the at least one audio signal
to a receiving device at a monitoring location. In addition to the
foregoing, other aspects of a computer program product including
one or more non-transitory machine-readable data storage media
bearing one or more instructions are described in the claims,
drawings, and text forming a part of the disclosure set forth
herein.
[0025] The foregoing summary is illustrative only and is not
intended to be in any way limiting. In addition to the illustrative
aspects, embodiments, and features described above, further
aspects, embodiments, and features will become apparent by
reference to the drawings and the following detailed
description.
BRIEF DESCRIPTION OF THE FIGURES
[0026] FIG. 1 is a block diagram of a system for monitoring
compliance of a patient with a treatment regimen.
[0027] FIG. 2 is a block diagram of an unobtrusive
activity-detection system.
[0028] FIG. 3 is a block diagram showing further details of the
unobtrusive activity-detection system of FIG. 2.
[0029] FIG. 4 is a block diagram of a monitoring system.
[0030] FIG. 5 illustrates an example embodiment of a thin computing
device in which embodiments may be implemented.
[0031] FIG. 6 illustrates an example embodiment of a computing
system in which embodiments may be implemented.
[0032] FIG. 7 is an illustration of an unobtrusive activity
detection system implemented in a cell phone.
[0033] FIG. 8 is an illustration of an unobtrusive activity
detection system implemented in a computing system.
[0034] FIG. 9 is an illustration of an unobtrusive activity
detection system implemented in a microwave oven.
[0035] FIG. 10 is an illustration of an unobtrusive activity
detection system implemented in a game system.
[0036] FIG. 11 is an illustration of an unobtrusive activity
detection system implemented in a vehicle system.
[0037] FIG. 12 is an illustration of an unobtrusive activity
detection system implemented in a kiosk.
[0038] FIG. 13 is an illustration of an unobtrusive activity
detection system implemented in an intercommunication system.
[0039] FIG. 14 is an illustration of an unobtrusive activity
detection system implemented in connection with a hair brush.
[0040] FIG. 15 is a flow diagram of a method relating to monitoring
compliance of a patient with a prescribed treatment regimen.
[0041] FIG. 16 is a flow diagram of further aspects of the method
of FIG. 15.
[0042] FIG. 17 is a flow diagram of further aspects of the method
of FIG. 15.
[0043] FIG. 18 is a flow diagram of further aspects of the method
of FIG. 15.
[0044] FIG. 19 is a flow diagram of further aspects of the method
of FIG. 15.
[0045] FIG. 20 is a flow diagram of further aspects of the method
of FIG. 15.
[0046] FIG. 21 is a flow diagram of further aspects of the method
of FIG. 15.
[0047] FIG. 22 is a flow diagram of further aspects of the method
of FIG. 15.
[0048] FIG. 23 is a flow diagram of further aspects of the method
of FIG. 15.
[0049] FIG. 24 is a flow diagram of further aspects of the method
of FIG. 15.
[0050] FIG. 25 is a flow diagram of further aspects of the method
of FIG. 15.
[0051] FIG. 26 is a flow diagram of further aspects of the method
of FIG. 15.
[0052] FIG. 27 is a flow diagram of further aspects of the method
of FIG. 15.
[0053] FIG. 28 is a flow diagram of further aspects of the method
of FIG. 15.
[0054] FIG. 29 is a block diagram of a computer program product
including a signal-bearing medium.
[0055] FIG. 30 is a block diagram of a system including a computing
device.
[0056] FIG. 31 is a flow diagram of a method of monitoring
compliance of a patient with a prescribed treatment regimen.
[0057] FIG. 32 is a flow diagram of further aspects of the method
of FIG. 31.
[0058] FIG. 33 is a flow diagram of further aspects of the method
of FIG. 31.
[0059] FIG. 34 is a flow diagram of further aspects of the method
of FIG. 31.
[0060] FIG. 35 is a flow diagram of further aspects of the method
of FIG. 31.
[0061] FIG. 36 is a flow diagram of further aspects of the method
of FIG. 31.
[0062] FIG. 37 is a flow diagram of further aspects of the method
of FIG. 31.
[0063] FIG. 38 is a flow diagram of further aspects of the method
of FIG. 31.
[0064] FIG. 39 is a flow diagram of further aspects of the method
of FIG. 31.
[0065] FIG. 40 is a flow diagram of further aspects of the method
of FIG. 31.
[0066] FIG. 41 is a flow diagram of further aspects of the method
of FIG. 31.
[0067] FIG. 42 is a flow diagram of further aspects of the method
of FIG. 31.
[0068] FIG. 43 is a flow diagram of further aspects of the method
of FIG. 31.
[0069] FIG. 44 is a flow diagram of further aspects of the method
of FIG. 31.
[0070] FIG. 45 is a flow diagram of further aspects of the method
of FIG. 31.
[0071] FIG. 46 is a flow diagram of further aspects of the method
of FIG. 31.
[0072] FIG. 47 is a flow diagram of further aspects of the method
of FIG. 31.
[0073] FIG. 48 is a flow diagram of further aspects of the method
of FIG. 31.
[0074] FIG. 49 is a block diagram of a computer program product
including a signal-bearing medium.
[0075] FIG. 50 is a block diagram of a system including a computing
device.
[0076] FIG. 51 is a block diagram system for monitoring compliance
of a patient with a treatment regimen.
[0077] FIG. 52 is a flow diagram of a method is a flow diagram of a
method of monitoring compliance of a patient with a prescribed
treatment regimen.
[0078] FIG. 53 is a block diagram of a computer program product
including a signal-bearing medium.
[0079] FIG. 54 is a block diagram of a system including a computing
device.
[0080] FIG. 55 is a flow diagram of a method of monitoring
compliance of a patient with a treatment regimen.
[0081] FIG. 56 is a block diagram of a computer program product
including a signal-bearing medium.
[0082] FIG. 57 is a block diagram of a system including a computing
device.
DETAILED DESCRIPTION
[0083] In the following detailed description, reference is made to
the accompanying drawings, which form a part hereof. In the
drawings, similar symbols typically identify similar components,
unless context dictates otherwise. The illustrative embodiments
described in the detailed description, drawings, and claims are not
meant to be limiting. Other embodiments may be utilized, and other
changes may be made, without departing from the spirit or scope of
the subject matter presented here.
[0084] In an aspect, a patient 102 has a brain-related disorder,
and treatment of the patient according to a prescribed treatment
regimen 104 results in detectable changes in the patient's
performance of one or more non-speech activities, relative to the
patient's activity performance while in an untreated or partially
treated state. In an aspect, failure of the patient to comply with
a prescribed treatment regimen can be detected by monitoring the
patient's activity-related activity patterns, and steps can be
taken to address the patient's lack of compliance. FIG. 1
illustrates in block diagram form a system 100 for monitoring
compliance of a patient 102 with a prescribed treatment regimen 104
based upon unobtrusive detection of a non-verbal activity of the
patient, where the non-verbal activity corresponds to performance
of non-speech activity 106 by the patient. System 100 includes
unobtrusive activity-detection system 108 at patient location 110,
which is used to detect non-verbal activity of the patient, and
monitoring system 112 at monitoring location 114, which allows
remote monitoring of patient compliance with prescribed treatment
regimen 104 by a medical care provider 170 or other interested
party or entity, e.g., a family member, an insurance company,
etc.
[0085] In FIG. 1, and in other figures herein, in general, unless
context dictates otherwise, solid lines are used to indicate
standard components or steps, and dashed lines are used to
represent optional components or steps. Unless context indicates
otherwise, dotted lines are used to indicate data or information.
Dashed lines may also be used to indicate signals.
[0086] System 100 monitors compliance of patient 102 with
prescribed treatment regimen 104 by detecting and analyzing
activity of patient 102 corresponding to performance of a
non-speech activity 106.
[0087] Unobtrusive activity-detection system 108 includes at least
one activity sensor 116 for sensing at least one activity signal
118 including a non-speech activity pattern 120 corresponding to
performance of non-speech activity 106 by patient 102 at patient
location 110. Unobtrusive activity-detection system 108 also
includes activity detection circuitry 122, which is configured to
identify at least one section 124 of the at least one activity
signal 118 containing the non-speech activity pattern 120, and
activity analysis circuitry 126 for processing the at least one
section 124 of the at least one activity signal 118 to generate
activity data 128 including data indicative of whether the patient
has complied with the treatment regimen. In addition, unobtrusive
activity-detection system 108 includes at least one transmitting
device 132 for transmitting activity data signal 134 including
activity data 128 including data indicative of whether the patient
has complied with the treatment regimen. Transmitting device 132
transmits activity data signal 134 from patient location 110 to
receiving device 136 at monitoring location 114.
[0088] Monitoring system 112 at monitoring location 114 includes at
least one receiving device 136 for use at a monitoring location 114
for receiving an activity data signal 134 transmitted to the
monitoring location 114 from patient location 110. Activity data
signal 134 contains activity data 128 representing at least one
non-speech activity pattern 120 in activity sensed from patient 102
with at least one activity sensor 116 in unobtrusive
activity-detection system 108 at patient location 110 during
performance of non-speech activity 106 by patient 102. Monitoring
system 112 also includes signal processing circuitry 150, which is
configured to analyze activity data signal 134 to determine whether
activity data 128 represents at least one non-speech activity
pattern 120 that matches at least one characteristic activity
pattern 152. Signal processing circuitry 150 generates match signal
154 indicating a determination that non-speech activity pattern 120
matches a characteristic activity pattern 152. Monitoring system
112 also includes compliance determination circuitry 156, which is
configured to determine whether patient 102 has complied with
prescribed treatment regimen 104 based upon whether activity data
128 represents a non-speech activity pattern 120 that matches at
least one characteristic activity pattern 152. Compliance
determination circuitry 156 generates compliance signal 158.
Monitoring system 112 also includes reporting circuitry 160, which
is configured to report a conclusion 162 (regarding patient's
compliance or lack thereof) based on the determination of whether
the patient has complied with the prescribed treatment regimen 104,
as indicated by compliance signal 158.
[0089] Both unobtrusive activity-detection system 108 and
monitoring system 112 include control/processing circuitry, e.g.,
control/processing circuitry 180 in unobtrusive activity-detection
system 108 and control/processing circuitry 190 in monitoring
system 112, which includes the circuitry components specifically
described herein and other circuitry components used to control
operation of unobtrusive activity-detection system 108 and
monitoring system 112, respectively.
[0090] In different embodiments, examples of which are described
elsewhere here, different levels of signal processing take place in
unobtrusive activity-detection system 108 at patient location 110
versus at monitoring system 112 at monitoring location 114. The
location at which different signal processing aspects are performed
may depend on availability of data storage space; speed,
reliability and/or power consumption of data transmission between
patient location 110 and monitoring location 114; and privacy
concerns relating to storage and transmittal of patient data, among
other considerations. As will be discussed in greater detail herein
below, activity data signal 134 may contain raw activity data,
information obtained from processed activity data, or both.
[0091] In an aspect, patient 102 has a brain-related disorder, and
prescribed treatment regimen 104 is a treatment regimen prescribed
to patient 102 for treating at least one aspect of the
brain-related disorder. Brain-related disorders include, for
example, mental disorders, psychological disorders, psychiatric
disorders, traumatic disorders, lesion-related disorders, and/or
neurological disorders, as discussed in greater detail elsewhere
herein. Prescribed treatment regimen 104 may include a prescription
for one or more therapeutic treatments, including medications,
pharmaceuticals, nutraceuticals, therapeutic activities, diet,
sleep, exercise, counseling, etc., to be used individually or in
combination. In various aspects, prescribed treatment regimen 104
specifies type, quantity, and time course of any or all such
therapeutic treatments.
[0092] Monitoring system 112 at monitoring location 114 allows
medical care provider 170 or another interested individual or
entity to remotely monitor compliance of patient 102 with
prescribed treatment regimen 104. Monitoring location 114 may be,
for example, a hospital, clinic, data center, or doctor's office.
Monitoring location 114 may be a short distance away from patient
location 110 (e.g., in another room of the same building, or even
within the same room as patient location 110) or it may be in a
separate building, a few miles away, or many miles away.
[0093] Systems as described herein can be used, for example, to
monitor patient compliance with prescribed treatment regimen 104 at
the request of or with the cooperation and/or authorization of
patient 102, e.g., in the situation that the patient and/or the
patient's caregiver wish to track the patient's compliance with the
prescribed treatment regimen. In some cases, monitoring of patient
compliance with a prescribed treatment regimen can be implemented
at the request or requirement of a caregiver, insurance company, or
other individual or entity, for example, as a condition of living
in a group home, mental health care facility, or other institution,
or as a condition of insurance reimbursement for treatment. In some
cases, monitoring of compliance can be implemented without
knowledge and/or authorization of the patient, e.g., in situations
in which the patient is not capable of making decisions for his or
her self or to fulfill a legal requirement.
[0094] FIG. 2 illustrates components of unobtrusive
activity-detection system 108 at patient location 110. As discussed
above, unobtrusive activity-detection system 108 includes at least
one activity sensor 116, activity detection circuitry 122, activity
analysis circuitry 126, and at least one transmitting device 132.
Activity detection circuitry 122, activity analysis circuitry 126,
and other circuitry components as described herein include or form
a part of control/processing circuitry 180.
[0095] Non-speech activity detected by unobtrusive
activity-detection system 108 corresponds to one or more non-speech
activity 106 performed by patient 102 (as shown in FIG. 1). For
example, such activities may include various activities of daily
life, or other activities or tasks performed routinely by patient
102, including, but not limited to, hygiene, washing, eating,
dressing, brushing teeth, brushing hair, combing hair, preparing
food, interacting with another person (e.g., in the same location
or via an electronic device), interacting with an animal,
interacting with a machine, interacting with an electronic device,
or using an implement. In an aspect, such activities are performed
by the patient 102 without prompting by unobtrusive
activity-detection system 108. In an aspect, detection of
non-speech activity-related activity is accomplished in a manner
that is not noticeable to the patient, and does not interfere with
the patient's daily routine. Unprompted activity refers to activity
that is performed independent of any prompt by unobtrusive
activity-detection system 108. Such activity can be considered
"passively captured" in that capture of such activity is not
predicated on the delivery of a prompt to the patient from
unobtrusive activity-detection system 108. It should be noted,
however, that, as used herein, unprompted activity in some cases
includes activity produced by the patient in response to prompts or
queries by another person, e.g., in the course of interaction with
the person. In addition, activity produced by the patient that is
not dependent on prior interaction with another person is also
considered "spontaneous activity."
[0096] Unobtrusive activity-detection system 108 may include
various types of sensors 226, including various types of activity
sensor(s) 116 for detecting activities that provide information
regarding the patient's brain-related state. The patient's
movements may be detected directly or indirectly with various types
of sensors (including, but not limited to, pressure, force,
capacitance, optical, motion, and acceleration sensors). Imaging
sensors (e.g., cameras) can provide images of the patient that can
be used to determine various aspects of motion of the patient. The
patient's interaction with devices may be detected with user
interface and input devices (e.g., keyboard, pointing device, or
touchscreen) and/or device controls (including, but not limited to,
controllers for game or entertainment devices or systems,
appliances, vehicles, medical equipment, etc.). Interaction of the
patient with other individuals, pets, or other animals, can be
detected through image analysis, or through the use of proximity
sensors to detect proximity of the patient to the individual or
animal (with proximity assumed to correlate with interaction).
Activity sensor 116 may be worn or carried by the patient, built
into or attached to a device with which the patient interacts, or
located in the patient's environment (e.g., a video camera in the
patient's home).
[0097] In an aspect, activity detection circuitry 122 is configured
to identity the at least one section 124 of the at least one
activity signal containing non-speech activity pattern 120 from an
activity signal 118 corresponding to unprompted performance of the
non-speech activity by the patient.
[0098] In an aspect, unobtrusive activity-detection system 108
includes timing circuitry 202 configured to control timing of
operation of at least a portion of unobtrusive activity-detection
system 108 to perform substantially continuously sensing the at
least one activity signal 118 with the at least one activity sensor
116. In an aspect, timing circuitry 202 includes a clock or timer
device. For example, timing circuitry 202 may be configured to
cause sensing to be performed substantially continuously by causing
samples to be collected from the activity sensor 116 (e.g., via an
A/D converter, not shown) at a fixed sampling rate that is
sufficiently high to capture any meaningful variations in the
activity sensed by the sensor (e.g., at at least the Nyquist rate).
The sampling rate may be determined by hardware or software, and
may be factory pre-set or controllable by the user (e.g., the
sampling rate may be determined by one or more control parameters
288 stored in data storage device 206, which may be set during
manufacture of unobtrusive activity-detection system 108, or
entered by a user of the system via input device 208.) For example,
in an aspect, control/processing circuitry 180 includes an A/D
converter, with the sampling rate of the A/D converter controlled
by timing circuitry 202.
[0099] In another aspect, timing circuitry 202 is configured to
control timing of operation of at least a portion of the system to
perform intermittently at least one of sensing the at least one
activity signal 118 with the at least one activity sensor 116,
identifying the at least one section 124 of the at least one
activity signal containing the non-speech activity pattern with the
activity detection circuitry 122, processing the at least one
section of the at least one activity signal to generate activity
data 128 including data indicative of whether the patient has
complied with the treatment regimen with the activity analysis
circuitry 126, and transmitting an activity data signal 134
including the activity data 128 including data indicative of
whether the patient has complied with the treatment regimen from
the patient location 110 to a receiving device at a monitoring
location with the at least one transmitting device 132. For
example, in an aspect, intermittent sensing of the at least one
activity signal 118 is controlled by using software to determine
sampling rate and times at which sampling is performed, with
appropriately selected control parameters 288 stored in data
storage device 206. Alternatively, in an aspect, activity is sensed
substantially continuously with activity sensor 116, but either
activity detection circuitry 122 and/or activity analysis circuitry
126 is configured to process the activity signal 118 and/or section
124 intermittently rather than continuously. In another aspect,
activity signal 118 is sampled on a substantially continuous basis,
but transmitting device 132 is configured (with hardware or
software) to transmit activity data signal 134 to the monitoring
location only intermittently (once an hour, once a day, etc.).
Intermittent performance of sampling, data transmission, and/or
other system functions include performance at uniform intervals,
any sort of non-uniform intermittent pattern (e.g., at a high
frequency during some parts of the day and lower frequency during
other parts of the day), or at random or quasi-random intervals
(e.g., as determined by a random number generator). In an aspect,
timing of system functions is controlled in part by timing
circuitry 202 and in part in response to some other sensed
parameter or other inputs; for example, a basic schedule may be
determined by timing circuitry 202 but if it is determined that the
subject is asleep or is not present, or if the data cannot be
transmitted due to low signal strength, low battery power, etc.,
the scheduled function may be delayed until suitable conditions are
obtained. Data storage device 206 is used to store data 210 that
includes any or all of activity signal 118, section 124 of activity
signal, and activity data 128, as such data are obtained. Data thus
stored can be retrieved from data storage device 206 for
transmission with transmitting device 132 intermittently. Data
storage device 206 may be any of various types of data storage
and/or memory devices.
[0100] In an aspect, timing circuitry 202 is configured to control
timing of operation of at least a portion of the system to perform
according to a schedule at least one of sensing the at least one
activity signal with the at least one activity sensor 116,
identifying the at least one section 124 of the at least one
activity signal containing the non-speech activity pattern 120 with
the activity detection circuitry 122, processing the at least one
section 124 of the at least one activity signal to generate
activity data 128 including data indicative of whether the patient
has complied with the treatment regimen the activity analysis
circuitry, and transmitting an activity data signal 134 including
the activity data including data indicative of whether the patient
has complied with the treatment regimen from the patient location
to a receiving device at a monitoring location with the at least
one transmitting device 132. Performance of the aforementioned
steps according to a schedule can be controlled by timing circuitry
202 configured by hardware and software, using control parameters
288, including sampling rate and times at which sampling,
processing of activity signal 118 and/or section 124, and
transmission of activity data signal 134 are to be performed. The
timing of these steps can be determined by control parameters 288,
which may be set or selected by a user, or preset during
manufacture of the device, as described above. Unobtrusive
activity-detection system 108 may include one or more power sources
(not shown), e.g., a battery, a plug for connecting to an
electrical outlet or communication port, e.g., a USB port, or any
of various other types of power sources.
[0101] As noted above, in an aspect, unobtrusive activity-detection
system 108 includes an input device 208. In various aspects, input
device 208 includes one or more of a user interface device 212,
which may be any of various types of user interface devices, or
data input device 214, which is a data input device adapted to
receive data from a computing device or other electrical circuitry.
Such data may be received by a wired connection or wireless
connection. In an aspect, input device 208 is used for receiving a
treatment signal 220 indicative of initiation of treatment of the
patient according to the treatment regimen. In an aspect, treatment
signal 220 is received from a user (either the patient or a
caregiver of the patient) via a user interface device 212. In
another aspect, treatment signal 220 is received via data input
device 214.
[0102] In an aspect, unobtrusive activity-detection system 108
includes patient identification circuitry 222, which is configured
to determine a presence of the patient from at least one identity
signal 224 sensed at the patient location, and to generate presence
signal 225 which is provided to activity detection circuitry 122.
In an aspect, an identity signal 412 is transmitted from
unobtrusive activity-detection system 108 to a monitoring system at
the monitoring location. Identity signal 412 may be the same as
identity signal 224, or may be a processed version of identity
signal 224. In implementations in which unobtrusive
activity-detection system 108 does not include patient
identification circuitry 222, identity signal 412 may be
transmitted to the monitoring location and processed by circuitry
there to determine identity/presence of the patient. In
implementations in which unobtrusive activity-detection system 108
include patient identification circuitry 222, identity signal 412
transmitted to the monitoring location so that the
presence/identity of the patient may be determined from either the
patient location or the monitoring location, or both, or the
identity signal may be used for other purposes.
[0103] As noted previously, unobtrusive activity-detection system
108 includes activity sensor 116. In some aspects, activity signal
118 sensed by activity sensor 116 functions not only as a source of
information regarding one or more activities performed by patient
102, but also as an identity signal 224 which is used to determine
the identity of patient 102. In an aspect, patient identification
circuitry 222 is configured to identify the at least one section
124 of the at least one activity signal containing the non-speech
activity pattern based at least in part on a determination of the
presence of the patient 102 by patient identification circuitry
222. In an aspect the at least one identity signal 224 includes at
least a portion of the at least one activity signal 118, and
patient identification circuitry 222 is configured to analyze the
activity signal 118 to identify at least a portion of the at least
one activity signal that resembles a known activity pattern of the
patient. Accordingly, in this example activity sensor 116 is also
identity signal sensor 228.
[0104] In order to use activity signal 118 as identity signal 224,
it may be necessary to process activity signal 118 to determine the
presence of the patient and simultaneously or subsequently process
activity signal 118 with activity detection circuitry 122 to
generate activity data 128. This can be accomplished by parallel
processing of activity signal 118 by patient identification
circuitry 222 and activity detection circuitry 122, or by
processing activity signal 118 first with patient identification
circuitry 222 and subsequently with activity detection circuitry
122. If the latter approach is used, generation of activity data
signal 134 may not take place strictly in real time. Activity data
signal 134 can be identified through the use of other types of
identity signal, as well, as described herein below.
[0105] In some aspects, identity signal sensor 228 is distinct from
activity sensor 116. In an aspect, unobtrusive activity-detection
system 108 includes an audio signal sensor 230 for sensing an audio
signal including speech from patient 102 at the patient location,
and patient identification circuitry 222 includes speech analysis
circuitry 232 for identifying at least a portion of the audio
signal that resembles known speech of the patient. In an aspect,
activity detection circuitry 122 is configured to identify the at
least one section of the at least one activity signal 118 by
activity in activity signal 118 that corresponds (e.g., spatially
and/or temporally) to the presence of patient 102 detected by
speech analysis circuitry 232. For example, a continuous speech
system may be used for identifying the speaker, as described in
Chandra, E. and Sunitha, C., "A Review on Speech and Speaker
Authentication System using Voice Signal Feature Selection and
Extraction," IEEE International Advance Computing Conference, 2009.
IACC 2009, Page(s): 1341-1346, 2009 (DOI:
10.1109/IADCC.2009.4809211), which is incorporated herein by
reference. In an aspect, patient identification circuitry 222 is
configured to analyze identity signal 224 to determine the presence
of the patient based on frequency analysis of the audio identity
signal. Magnitude or phase spectral analysis may be used, as
described in McCowan, I.; Dean, D.; McLaren, M.; Vogt, R.; and
Sridharan, S.; "The Delta-Phase Spectrum With Application to Voice
Activity Detection and Speaker Recognition," IEEE Transactions on
Audio, Speech, and Language Processing, 2011, Volume: 19, Issue: 7,
Page(s): 2026-2038 (DOI: 10.1109/TASL.2011.2109379), which is
incorporated herein by reference.
[0106] In an aspect, unobtrusive activity-detection system 108
includes an imaging device 234 for sensing an image at the patient
location, wherein the patient identification circuitry 222 includes
image analysis circuitry 236 for identifying a presence of the
patient in the image. For example, in an aspect image analysis
circuitry 236 includes facial recognition circuitry 238, configured
to analyze the image to determine the presence of the patient
through facial recognition. For example, in an aspect facial
recognition circuitry 238 uses approaches as described in Wheeler,
Frederick W.; Weiss, R. L.; and Tu, Peter H., "Face Recognition at
a Distance System for Surveillance Applications," Fourth IEEE
International Conference on Biometrics: Theory Applications and
Systems (BTAS), 2010 Page(s): 1-8 (DOI: 10.1109/BTAS.2010.5634523),
and Moi Hoon Yap; Ugail, H.; Zwiggelaar, R.; Rajoub, B.; Doherty,
V.; Appleyard, S.; and Hurdy, G., "A Short Review of Methods for
Face Detection and Multifractal Analysis, " International
Conference on CyberWorlds, 2009. CW '09. , Page(s): 231-236 (DOI:
10.1109/CW.2009.47), both of which are incorporated herein by
reference.
[0107] In an aspect, image analysis circuitry 236 includes
gait/posture recognition circuitry 240, which is configured to
analyze the image to determine the presence of the patient through
gait or posture recognition. Identification of the patient based on
gait analysis can be performed, for example, by methods as
described in U.S. Pat. No. 7,330,566, issued Feb. 12, 2008 to
Cutler, and Gaba, I. and Kaur P., "Biometric Identification on The
Basis of BPNN Classifier with Other Novel Techniques Used For Gait
Analysis," Intl. J. of Recent Technology and Engineering (IJRTE)
ISSN: 2277-3878, Vol. 2, issue 4, September 2013, pp. 137-142, both
of which are incorporated herein by reference.
[0108] In an aspect, unobtrusive activity-detection system 108
includes a biometric sensor 242 for sensing a biometric signal from
the patient, wherein the patient identification circuitry 222
includes biometric signal analysis circuitry 244 for analyzing the
biometric signal to determine the presence of the patient.
Biometric identification can include face and gait recognition, as
described elsewhere herein, and recognition based on a variety of
other physiological or behavioral characteristics, such as
fingerprints, voice, iris, retina, hand geometry, handwriting,
keystroke pattern, etc., e.g., as described in Kataria, A. N.;
Adhyaru, D. M.; Sharma, A. K.; and Zaveri, T. H., "A Survey of
Automated Biometric Authentication Techniques" Nirma University
International Conference on Engineering (NUiCONE), 2013, Page(s):
1-6 (DOI: 10.1109/NUiCONE.2013.6780190), which is incorporated
herein by reference. U.S. Pat. No. 8,229,178 issued Jul. 24, 2012
to Zhang et al., which is incorporated herein by reference,
describes a method for acquiring a palm vein image with visible and
infrared light and extracting features from the image for
authentication of individual identity. Biometric identification can
be based on imaging of the retina or iris, as described in U.S.
Pat. No. 5,572,596 issued to Wildes et al. on Nov. 5, 1996 and U.S.
Pat. No. 4,641,349 issued to Flom et al. on Feb. 3, 1987, each of
which is incorporated herein by reference. Combinations of several
types of identity signals can also be used (e.g., speech and video,
as described in Aleksic, P. S. and Katsaggelos, A. K. "Audio-Visual
Biometrics," Proceedings of the IEEE Volume: 94, Issue: 11,
Page(s): 2025-2044, 2006 (DOI: 10.1109/JPROC.2006.886017), which is
incorporated herein by reference).
[0109] In an aspect, user interface device 212 is used for
receiving an input indicative of at least one authentication factor
from the user, and patient identification circuitry 222 includes
authentication circuitry 246 for determining the presence of the
patient based on the at least one authentication factor. The at
least one authentication factor may include, for example, a
security token, a password, a digital signature, and a
cryptographic key. In an aspect, an authentication factor is
received by unobtrusive activity-detection system via a user
interface device 212. User interface device 212 can include various
types of user interface devices or controls as are well known to
those of ordinary skill in the art, including, but not limited to,
keyboards, touchpads, touchscreens, pointing devices, (e.g., a
mouse), joysticks, tracking balls, graphic interfaces, styluses,
microphones or other voice interfaces, motion tracking interfaces,
gesture interfaces (e.g., via a Kinect.RTM. or the like),
brain-computer interfaces, buttons, or switches. User interface
device 212 can be integral to a communication device, e.g., a key
pad of a cell phone. One or more user interface device 212 in
unobtrusive activity-detection system 108 can be used to receive
various types of user interfaces relating to operation of
unobtrusive activity-detection system 108, not limited to entry of
an authentication factor. In an aspect, data input device 214 is
used to receive a data signal, which is used as the identity
signal, and patient identification circuitry 222 is configured to
determine the presence of the patient based on the data signal.
[0110] In an aspect, unobtrusive activity-detection system 108
includes a receiver 300 for receiving a cell phone identification
code, wherein the identity signal 224 is a cell phone
identification code, and wherein the patient identification
circuitry 222 is configured to determine the presence of the
patient based on the cell phone identification code. The cell phone
identification code may be, for example, an electronic serial
number, a mobile identification number, and a system identification
code.
[0111] In an aspect, unobtrusive activity-detection system 108
includes a radio frequency identification (RFID) sensor 252 for
receiving an RFID signal from an RFID device 253 carried by or
otherwise associated with patient 102, wherein the identity signal
224 is an RFID signal, and wherein the patient identification
circuitry 222 is configured to determine the presence of the
patient based on the RFID signal. In an aspect, RFID device 253 is
a passive RFID in a tag or chip associated with the patient. In an
aspect, RFID sensor 252 is an active RFID reader.
[0112] In an aspect, patient identification circuitry 222 is
configured to distinguish the presence of patient 102 from the
presence of another individual. In the event that the activity of
another individual is detected by unobtrusive activity-detection
system 108, activity detected from the other individual should not
be used to determine the compliance of patient 102 with prescribed
treatment regimen 104. Accordingly, in an aspect, patient
identification circuitry 222 is configured to determine the
presence of patient 102 by determining that information contained
in the identity signal matches patient information associated with
the patient. For some types of identity signal (e.g., a password or
device identity code), an exact match can be obtained. In other
cases, a match is obtained by using a windowing, thresholding, or
distance measurement to determine whether the identity signal (or
information contained there) matches sufficiently closely patient
information associated with the patient. In an aspect, patient
identification circuitry 222 is configured to distinguish the
presence of the patient from the absence of the patient.
[0113] In an aspect, patient identification circuitry 222 generates
presence signal 225 to indicate presence and/or identity of patient
102. In an aspect, presence signal 225 is provided as an input to
activity detection circuitry 122. Presence of patient 102 may be
indicated by a value of presence signal 225. For example, in some
aspects, presence signal 225 is a binary signal; e.g., presence
signal 225 has a high value if the patient is present or a low
value if the patient is not present (or vice versa). In an aspect,
activity data 128 is generated from activity signal 118 only when
the value of presence signal 225 indicates that patient 102 is
present. Alternatively, in some aspects presence signal 225 is a
continuous valued signal that indicates the probability that the
patient is present. For example, presence signal 225 has a value of
100 if there is 100 percent probability that the patient is
present, a value of zero if there is zero percent probability that
the patient is present, or an intermediate value if there is an
intermediate probability that the patient is present. It will be
appreciated that in some contexts, the determination of whether the
patient is present or absent will be relatively straightforward, in
which case a binary presence signal may be appropriate, whereas in
others (e.g., in cases where the presence of the patient must be
distinguished from the presence of other individuals, e.g., from a
conference call) there is some likelihood of error in identifying
the presence of the patient (with the likelihood of error
potentially dependent upon the number and identity of the other
individuals present), such that an indication of the probability
that the patient is present may be more appropriate. In some
aspects, various device functions (e.g., acquisition of activity
data, performance of activity analysis, or transmission of activity
data signal 134 to the monitoring location) are initiated in
response to detection of the presence of patient 102. In some
aspects, presence of patient 102 is a necessary but not sufficient
condition for performance of particular device functions. For
example, data may be collected at certain times of day, contingent
upon the presence of patient 102. In another aspect, data is
collected when patient 102 is present and initiates a particular
activity.
[0114] In an aspect, activity detection circuitry 122 is configured
to process the at least one activity signal to exclude at least one
portion of the at least one activity signal that does not contain
activity of patient 102, e.g., by excluding portions of the signal
that contain no activity, or that contain activity of someone other
than patient 102.
[0115] In an aspect, activity detection circuitry 122 is configured
to identify at least one section 124 of the at least one activity
signal containing an activity pattern corresponding to performance
of an activity of daily life, for example, hygiene, washing,
eating, dressing, brushing teeth, brushing hair, combing hair,
preparing food, interacting with another person, interacting with
an animal, interacting with a machine, interacting with an
electronic device, or using an implement.
[0116] In an aspect, activity detection circuitry 122 is configured
to identify at least one section of the at least one activity
signal containing an activity pattern corresponding to performance
of a motor activity. Examples of motor activities are typing,
providing an input via an input device, providing an input via a
keyboard, providing an input via a touchscreen, providing an input
via a pointing device, controlling an entertainment device or
system, controlling a game device or system, controlling a vehicle
system, or walking
[0117] In an aspect, unobtrusive activity-detection system 108
includes one or more physiological sensors 332. In some aspects,
physiological sensor 332 provides physiological activity signal 380
to activity detection circuitry 122. In an aspect, information from
physiological activity signal 380, taken in combination with
activity signal 118, provides supplemental information that aids in
determining compliance of patient 102 with prescribed treatment
regimen 104. In some aspects, physiological activity data signal
382, including physiological activity data based on information
from physiological activity signal 380 is transmitted to a
monitoring system for further analysis.
[0118] In an aspect, activity analysis circuitry 126 is configured
to process the at least one section 124 of the at least one
activity signal to determine at least one non-speech activity
pattern 120 of the patient. In an aspect, activity analysis
circuitry 126 is configured to generate activity data 128 that
includes the at least one non-speech activity pattern 120 of the
patient. In addition, in an aspect, activity analysis circuitry 126
includes an activity analyzer 250 for assessing the at least one
activity pattern to determine at least one activity parameter 252
indicative of whether the patient has complied with the treatment
regimen, and wherein the activity analysis circuitry 126 is
configured to generate activity data 128 that includes the at least
one activity parameter. In various aspects, activity analysis
circuitry 126 is configured to determine activity patterns or
parameters. In an aspect, an activity pattern characterizes one or
both of coarse and fine temporal patterns of activity (e.g.,
whether an activity occurs at a particular time of day, such as
morning, afternoon, evening, or night; frequency of occurrence of
the activity during a particular time window). In an aspect, an
activity pattern characterizes amplitude or intensity of the
activity (e.g., how forcefully the patient strikes a key on a
keyboard, or magnitude of body movement). In an aspect, an activity
pattern includes the location at which an activity is performed. In
an aspect, an activity pattern includes details regarding the
substance of the activity (e.g., if the activity is selecting a
song on a music player, the activity pattern includes information
regarding the specific song selected). Activity parameters may
include, but are not limited to, activity performance error rate,
activity performance rate, activity performance time, activity
performance frequency (e.g., repetitions of an activity), activity
performance variability (including amount of variability, or lack
thereof), or activity performance accuracy.
[0119] In an aspect, activity analysis circuitry 126 includes a
comparator 254 for comparing the at least one non-speech activity
pattern 120 with at least one characteristic activity pattern 256
to determine whether the patient has complied with the treatment
regimen. In an aspect, comparator 254 is configured to compare
non-speech activity pattern 120 with a plurality of characteristic
activity patterns 256, 258, and 260 (three characteristic activity
patterns are provided as an example but the comparison is not
limited to any specific number of characteristic activity
patterns).
[0120] In an aspect, activity analysis circuitry 126 is configured
to determine that the patient 102 has failed to comply with the
treatment regimen. In an aspect, activity analysis circuitry 126 is
configured to determine that the patient has complied with the
treatment regimen.
[0121] In an aspect, activity analysis circuitry 126 is configured
to determine whether the patient has complied with the treatment
regimen based upon a determination of whether the activity data 128
represents at least one of a plurality of characteristic activity
pattern(s) 262, 264, and 266. (Again, three patterns are provided
as examples but comparison can be made to any number of
characteristic activity patterns).
[0122] The result of the comparison performed by comparator 254 is
a determination that the activity data 128 (or non-speech activity
pattern 120 or activity parameter 252 derived therefrom) either
does, or does not, match one or more characteristic activity data
sets 256, 258, 260, patterns 262, 264, 266, or parameters 268, 270,
272. It will be appreciated that in various aspects, activity
analysis circuitry 122 can be configured to determine both
compliance and non-compliance, and additionally, or alternatively,
level of compliance (either at specific levels or simply partial
compliance). In an aspect, if there is a match, notification 291 is
generated by notification circuitry 290 regarding whether the
patient has complied with the prescribed treatment regimen. In
practice, the comparison performed by comparator 254 (which may
include thresholding, windowing, distance computation, for example,
as discussed herein above) will result in production of a signal
that indicates at least whether the patient has complied with the
prescribed treatment regimen, and alternatively, or in addition, a
level of compliance with the prescribed treatment regimen. In some
cases, a medical care provider at the monitoring location (or
another party or entity concerned with the patient's health and
well-being, such as a parent, family member, caretaker, healthcare
provider, insurance company, etc.) is notified only if the patient
has failed to comply with the prescribed treatment regimen.
Alternatively, in some aspects the medical care provider or other
party/entity is notified when the patient is in compliance with the
prescribed treatment regimen. In some aspects, notification can be
provided by transmitting a notification 291 generated by
notification circuitry 290 to the monitoring location with
transmitting device 132, or to a wireless device, e.g., a remote
device at the patient location, using wireless notification
circuitry 294.
[0123] In an aspect, transmitting device 132 includes a wireless
transmitter 270, which may, for example, transmit a signal to a
wireless router 272 or a cellular network 274. In another aspect,
transmitting device 132 includes a computer network connection 276,
e.g., an Ethernet connection 278. In another aspect, transmitting
device 132 includes a communication port 280. Communication port
280 may provide for communication with a computer drive 282 or USB
device 284.
[0124] In an aspect, unobtrusive activity-detection system 108
includes notification circuitry 290 for generating a notification
291 indicative of whether the patient has complied with the
treatment regimen. Notification circuitry 290 may include, for
example, email generation circuitry 292 for generating an email
notification, wireless notification circuitry 294 for generating a
notification to be transmitted to a wireless device, data storage
circuitry 296 for storing a notification in a data storage device,
and audio alarm circuitry 298 for generating an audio notification
to be delivered with audio source 299.
[0125] Compliance or lack thereof can be represented by appropriate
text or numerical value in a displayed report or email, e.g.,
reported by notification circuitry 290, or represented by a binary
value in data stored by data storage device 206. Alternatively, or
in addition, level of compliance can be represented by a continuous
value (e.g., percent compliance) or a text descriptor selected from
a number of text descriptors corresponding to different levels of
compliance (e.g., "non-compliance," "low compliance," "intermediate
compliance," "near-full compliance," "full compliance"). In an
aspect, notification circuitry 290 provides for formatting data
included in notification 291 appropriately (e.g., by including
appropriate text to accompany numerical data values) and for
deciding whether and how to report the conclusion, based upon user
preferences. For example, who is notified (patient versus medical
care provider versus family member) or how notification is provided
(stored in an event record, via email, or via a text message to a
cell phone) may depend on the patient's level of compliance and the
specifics of the patient. In some aspects, notification circuitry
290 can generate different levels of notifications depending on how
serious a problem non-compliance is likely to be for the patient.
Generating a notification may include retrieving a stored
notification 286 from data storage device 206, e.g., selected from
among one or more notifications 286 stored in data storage device
206. Notifications may take the form of text or numerical codes,
for example.
[0126] In an aspect, notification circuitry 290 includes audio
alarm circuitry 298 for generating an audio alarm, e.g., a tone or
voice alert to be delivered via an audio source (e.g., a speaker,
bell, buzzer, beeper, or the like). In an aspect, notification
circuitry 290 provides a notification to patient 102, e.g., by
generating an audio alarm via the audio source or causing a text
message to be displayed on a display of unobtrusive
activity-detection system 108, or a device in communication
therewith, e.g., a cell phone or computing system used by patient
102. A notification to the patient could take the form of a
reminder to take a medication or contact a medical care provider,
for example. In another aspect, notification circuitry 290 uses
wireless notification circuitry 294 to transmit a notification
(e.g., via wireless transmitter 270) to a wireless device such as a
pager, cell phone, or other wireless device used by a medical care
provider or family member interested in tracking the status of the
patient. In another aspect, notification circuitry 290 includes
data storage circuitry 296 for storing a notification in a data
storage device 206. For example, in an aspect, data storage device
206 provides for storage of a notification in event history 297 in
conjunction with information regarding the time at which the
notification was generated (obtained, for example from timing
circuitry 202). In an aspect, information stored in event history
297 becomes a part of the subject's electronic medical records, and
may ultimately be transferred to the monitoring system or other
location. In an aspect, timing circuitry 202 includes a clock
and/or timer, for example.
[0127] FIG. 3 depicts details of unobtrusive activity-detection
system 108, showing additional details and additional and/or
alternative components relative to what is shown in FIG. 2. As
discussed in connection with FIG. 2, unobtrusive activity detection
system 108 includes a variety of sensors 226, including one or more
activity sensor 116 and one of more identity signal sensor 228. As
discussed in connection with FIG. 2, in some aspects activity
sensor 116 is the same as identity signal sensor 228, while in
other aspects the activity and identity signal sensors are
different sensors. Sensors 226 may include one or more identity
signal sensor 228, including, but not limited to, one or more audio
signal sensor 230, biometric sensor 242, RFID sensor 252, or
imaging device 234. In an aspect, activity sensor 116 includes a
camera 318 or other imaging device 234, which, in combination with
appropriate hardware and software, may form a motion capture device
(e.g., a Kinect.RTM.- or PlayStation.RTM. 4 Camera-type controller)
that detects movements and/or gestures. In various aspects, such
devices include depth sensing and IR reflectance technology,
built-in color camera, infrared (IR) emitter, and microphone
array.
[0128] A motion capture device can be used to detect activity of
the subject during gaming or during daily living activities. In
various aspects, camera 318 includes 2D and 3D cameras. Activity
sensor 116 includes one or more devices of one or more types
capable of sensing activity of the patient. In various aspects, the
at least one activity sensor 116 includes one or more input device
208 (as described in connection with FIG. 2 which may be, for
example, a keyboard 302, a pointing device 304 (e.g., a computer
mouse), or a touchscreen 306. In various aspects, the at least one
activity sensor 116 includes one or more remote controller for an
entertainment device or system 308, or game controller 310. In
various aspects, the at least one activity sensor includes a
user-activated sensor in a vehicle system 312. In an aspect,
activity sensor 116 is a wearable sensor 314 or an environmental
sensor 316. In an aspect, an environmental sensor 316 includes one
or more optical sensor 326 or camera 318 or other imaging device
234, in the environment of the subject. In an aspect, an
environmental sensor includes a sensor in the environment of the
subject that senses proximity of the patient to an object in the
environment. In an aspect, an environmental sensor is a sensor
attached to an animal or person in the environment. In an aspect,
activity sensor 116 is attached to an item which the patient uses
or interacts with, e.g., a comb, a toothbrush, an implement, a
utensil, a tool, keys, etc. In an aspect, the at least one activity
sensor 116 includes an imaging device 234, which may be, for
example, a camera 318. In other aspect, activity sensor 116
includes one or more pressure sensor 320, force sensor 322,
capacitive sensor 324, optical sensor 326, motion sensor 328, or
acceleration sensor 330.
[0129] In an aspect, unobtrusive activity-detection system 108
includes at least one physiological sensor 332, operatively
connected to the unobtrusive activity-detection system and
configured to detect a physiological signal indicative of whether
the patient has complied with the treatment regimen. For example,
in an aspect, physiological sensor 332 includes an EEG sensor 334.
In an aspect, EEG sensor 334 is configured to detect an
event-related potential. Event-related potentials, or "ERPs"
correspond to attention of a subject to an event (e.g., the event
captures the subject's interest). ERPs normally occur at a fixed
latency relative to the event of interest; thus, if the time of
occurrence of the event of interest is known, ERGs can be detected
based on their latency relative to the event of interest. In
addition, it is also possible to detect ERPs in the EEG based on
their characteristic shape, without information regarding when the
event of interest occurred. Various ERP parameters, such as
amplitude, latency, and/or topography are changed in patients with
brain-related disorders. See, e.g., Hansenne, "Event-Related Brain
Potentials in Psychopathology: Clinical and Cognitive
Perspectives," Psychologica Belgica 2006, vol. 46, iss. 1-2, pp.
5-36, and Wise et al., "Event-Related Potential and Autonomic Signs
of Maladaptive Information Processing During an Auditory Oddball
Task in Panic Disorder," International Journal of Psychophysiology
74 (2009) 34-44, both of which are incorporated herein by
reference. Moreover, in some cases treatment of brain-related
disorder, e.g., with pharmaceuticals, at least partially restores
the ERP parameters to values observed in individuals without the
disorder, as described in Sumiyoshi et al., "Neural Basis for the
Ability of Atypical Antipsychotic Drugs to Improve Cognition in
Schizophrenia," Frontiers in Behavioral Neuroscience," 16 Oct.
2013, Volume 7, Article 140, which is incorporated herein by
reference. In an aspect, the number and/or nature of ERPs detected
in the patient's EEG provides additional or alternative information
regarding compliance of the patient with the treatment regimen. In
other aspects, physiological sensor 332 includes a heart rate
sensor 336, an eye position sensor 338, or a pupil diameter sensor
340. Heart rate can be sensed by various approaches, using sensors
in a fitness band (for example, of the type described in U.S. Pat.
No. 9,113,795, which is incorporated herein by reference), sensors
attached to the skin, etc. using various methods known in the art.
Eye position can be sensed using a method and system as described
in U.S. Pat. No. 8,808,195 to Tseng et al., which is incorporated
herein by reference, or by other methods described herein or known
to those skilled in the relevant art. Eye position may include
static or fixed eye position/gaze direction or dynamic eye
position/eye movement. Pupil diameter can be measured, for example,
by methods as described in U.S. Pat. No. 6,162,186 to Scinto et
al., which is incorporated herein by reference. Abnormal pupillary
function is observed, for example, in patients with Alzheimer's
disease (As discussed in Fotiou et al., "Pupil Reaction to Light in
Alzheimer's disease: Evaluation of Pupil Size Changes and
Mobility", Aging Clin Exp Res 2007 October; 19(5):364-71
(Abstract), which is incorporated herein by reference.
[0130] Unobtrusive activity-detection system 108 can be constructed
and implemented in a variety of embodiments in which different
devices and/or device components provide the functionality
described herein. In an aspect, unobtrusive activity-detection
system 108 includes or is implemented on or in connection with
various types of systems with which the patient interacts. In an
aspect, unobtrusive activity-detection system 108 is built into
such a user-interactive system 350. In another aspect, unobtrusive
activity-detection system 108 is constructed separately but used in
combination with such a user-interactive system 350. For example,
unobtrusive activity-detection system 108 may be attached to
user-interactive system 350, or operatively connected to
user-interactive system 350. In various aspects, unobtrusive
activity-detection system 108 can be constructed as a
microprocessor-based system, either as a device that provides
compliance monitoring in combination with some other functionality,
or as a compliance monitoring system that is used independently, or
as an add-on to a system which provides some other
functionality.
[0131] In an aspect, activity sensor 116, activity detection
circuitry 122, activity analysis circuitry 126, and transmitting
device 132 are components of a cell phone 352 configured with
application software. In another aspect, activity sensor 116,
activity detection circuitry 122, activity analysis circuitry 126,
and transmitting device 132 are components of a computing device or
system 354. In another aspect, activity sensor 116, activity
detection circuitry 122, activity analysis circuitry 126, and
transmitting device 132 are components of an appliance 356 (e.g., a
household appliance such as a microwave oven, a washing machine, or
a coffee maker). In another aspect, activity sensor 116, activity
detection circuitry 122, activity analysis circuitry 126, and
transmitting device 132 are components of an entertainment device
or system 358 (e.g., a TV, a DVD player, or a music player) or a
game device or system 360. In yet another aspect, activity sensor
116, activity detection circuitry 122, activity analysis circuitry
126, and transmitting device 132 are components of a vehicle system
362. In an aspect, activity sensor 116, activity detection
circuitry 122, activity analysis circuitry 126, and transmitting
device 132 are components of a kiosk 364. In particular, kiosk 364
may be a medical kiosk used to provide health-related information,
perform medical monitoring (e.g., take a blood pressure reading),
dispense medication, and the like. In another example, kiosk 364
may be an entertainment or gaming kiosk, for example, located in a
public venue such as a shopping mall or airport. In another aspect,
activity sensor 116, activity detection circuitry 122, activity
analysis circuitry 126, and transmitting device 132 are components
of an intercommunication ("intercom") system 366. In another
aspect, activity sensor 116, activity detection circuitry 122,
activity analysis circuitry 126, and transmitting device 132 are
components of a personal item 368. For example, personal item 368
can be any of various types of personal items that are used by the
patient in the course of carrying out activities of daily life,
such that the patient's interaction with personal item 368 may
indicate compliance of the patient with a prescribed treatment
regimen. For example, personal item 368 may be a personal grooming
article such as a comb, hair brush, or toothbrush; a tool or
implement; a key or a key fob attached to one or more keys; a
wearable item such as a wristwatch, an item of jewelry, eyeglasses,
an article of clothing, footwear, hat, helmet, head covering, or
hairband; or a wallet or purse. In an aspect, one or more of
activity sensor 116, activity detection circuitry 122, activity
analysis circuitry 126, and transmitting device 132 are operatively
connected to personal item 368; e.g., one or more components may be
packaged separately from personal item 368 but configured to be
physically attached to personal item 368. In some aspects, one or
more components of unobtrusive activity detection system 108 are
not attached to the personal item 368, but communicate with at
least one component attached to or built into personal item
368.
[0132] In addition to activity sensor 116, activity detection
circuitry 122, activity analysis circuitry 126, and transmitting
device 132 that form part of unobtrusive activity-detection system
108, user-interactive system 350 includes device function-related
components 370, including, but not limited to, mechanical
components 372 and/or circuitry 374, which may include hardware
376, software 378, and/or microprocessor 380.
[0133] FIG. 4 depicts aspects of monitoring system 112. As
described briefly in connection with FIG. 1, monitoring system 112
includes at least one receiving device 136 for use at a monitoring
location 114 for receiving an activity data signal 134 transmitted
to monitoring location 114 from a patient location. Activity data
signal 134 contains activity data 128 representing at least one
non-speech activity pattern 120 in activity sensed from a patient
with at least one activity sensor in an unobtrusive
activity-detection system (e.g., unobtrusive activity-detection
system 108 at patient location 110 as shown in FIG. 1) during
performance of the non-speech activity by the patient. Monitoring
system 112 also includes signal processing circuitry 150, which is
configured to analyze activity data signal 134 to determine whether
the activity data 128 represents at least one non-speech activity
pattern 120 that matches at least one characteristic activity
pattern 152. In addition, monitoring system 112 includes compliance
determination circuitry 156 configured to determine whether the
patient has complied with the prescribed treatment regimen based
upon whether the activity data 128 represents the non-speech
activity pattern 120 that matches the at least one characteristic
activity pattern 152, and reporting circuitry 160 configured to
report a conclusion 162 based on the determination of whether the
patient has complied with the treatment regimen.
[0134] In an aspect, signal processing circuitry 150 is configured
to analyze the activity data signal 134 to identify at least one
non-speech activity pattern that corresponds to unprompted
performance of the non-speech activity by the patient. For example,
in an aspect, signal processing circuitry 150 identifies non-speech
activity based upon detectable patterns in the activity data
signal, without relying upon information regarding timing of
activity relative to a prompt. Analysis of activity data and/or
activity patterns is performed substantially as discussed in
connection with activity analysis circuitry 126 in FIG. 2.
[0135] In an aspect, monitoring system 112 includes timing
circuitry 402, which may include a clock or timer device, and
function in a manner substantially similar to timing circuitry 202
in unobtrusive activity-detection system 108 as described in
connection with FIG. 2. In an aspect, timing circuitry 402 is
configured to control timing of operation of at least a portion of
the system to perform substantially continuously the operation of
receiving the activity data signal 134 with the at least one
receiving device 136. Receiving activity data signal 134
substantially continuously includes receiving a signal
substantially without interruption, or sampling activity data
signal 134 at a rate that is sufficiently high to capture any
meaningful variations in the activity sensed by the sensor, as
discussed herein above in connection with timing circuitry 202. In
an aspect, timing circuitry 402 is configured to control timing of
operation of at least a portion of monitoring system 112 to perform
intermittently at least one of receiving the activity data signal
134 with the at least one receiving device 136, analyzing the
activity data signal 134 with signal processing circuitry 150,
determining with compliance determination circuitry 156 at
monitoring location 114 whether the patient has complied with the
treatment regimen, and reporting with reporting circuitry 160 a
conclusion 162 based on the determination of whether the patient
has complied with the prescribed treatment regimen.
[0136] In another aspect, timing circuitry 402 is configured to
control timing of operation of at least a portion of the system to
perform according to a schedule at least one of receiving the
activity data signal 134 with the at least one receiving device
136, analyzing the activity data signal 134 with signal processing
circuitry 150, determining with compliance determination circuitry
156 at the monitoring location 114 whether the patient has complied
with the treatment regimen, and reporting with reporting circuitry
160 a conclusion 162 based on the determination of whether the
patient has complied with the prescribed treatment regimen. Timing
of operation of monitoring system 112 to form operations
intermittently or according to a schedule can be controlled by
timing circuitry 402 configured by hardware and software, using
control parameters which may be set or selected by a user, or
preset during manufacture of the device, as described above.
[0137] In some aspects, non-speech activity pattern 120 is an
activity pattern corresponding to performance of a motor activity,
which may include, for example, typing, providing an input via an
input device, providing an input via a keyboard, providing an input
via a touchscreen, providing an input via a pointing device,
controlling a game device or system, controlling an entertainment
device or system, controlling a vehicle system, or walking In some
aspects, non-speech activity pattern 120 is an activity pattern
corresponding to performance of an activity of daily life, for
example, hygiene, washing, eating, dressing, brushing teeth,
brushing hair, combing hair, preparing food, interacting with
another person, interacting with an animal, interacting with a
machine, interacting with an electronic device, or using an
implement.
[0138] In various aspects, activity data signal 134 contains
activity data 128 including data from various types of sensors, as
described in connection with FIG. 3, e.g., a pressure sensor, a
force sensor, a capacitive sensor, an imaging device, a motion
sensor, a motion capture device, an acceleration sensor, an optical
sensor, a camera. In various aspects, activity data 128 represents
one or more of a keystroke pattern, an activity performance
pattern, an activity performance rate, an activity performance
time, an activity performance frequency, an activity performance
variability, an activity performance accuracy, or an activity
performance error rate.
[0139] In an aspect, monitoring system 112 includes patient
identification circuitry 410, which is configured to determine a
presence of the patient from at least one identity signal 412
received by receiving device 136 at the monitoring location 114
from the patient location; in connection therewith signal
processing circuitry 150 is configured to identify patient activity
data corresponding to an activity of the patient based at least in
part on the determination of the presence of the patient by the
patient identification circuitry, as indicated by presence signal
414 generated by patient identification circuitry 410. In general,
identity signals and determination of the presence of the patient
are as described herein above in connection with FIG. 2.
[0140] In an aspect, identity signal 412 includes at least a
portion of the activity data 128 in activity data signal 134,
wherein patient identification circuitry 410 includes activity
analysis circuitry 416 configured to analyze the activity data 128
to identify at least a portion of the activity data signal 134
containing activity data representing an activity pattern that
matches a known activity pattern of the patient.
[0141] In an aspect, identity signal 412 includes a voice signal
received from an audio sensor at the patient location, patient
identification circuitry 410 includes speech analysis circuitry 418
for identifying at least a portion of the audio signal that
resembles known speech of the patient, and signal processing
circuitry 150 is configured to identify activity data corresponding
to an activity of the patient by identifying activity data
corresponding to a portion of the audio signal that resembles known
speech of the patient.
[0142] In an aspect, identity signal 412 includes an image signal
received from an imaging device at the patient location, wherein
the patient identification circuitry includes image analysis
circuitry 420 configured to analyze the image signal to determine
the presence of the patient, and wherein the signal processing
circuitry 150 is configured to identify activity data corresponding
to an activity of the patient by identifying activity data
corresponding to an image signal indicative of the presence of the
patient. Image analysis circuitry 420 may include facial
recognition circuitry 422 configured to analyze the image signal to
determine the presence of the patient through facial recognition,
or gait or posture analysis circuitry 424 configured to analyze the
image signal to determine the presence of the patient through gait
or posture recognition.
[0143] In another aspect, identity signal 412 includes a biometric
signal from at least one biometric sensor at the patient location,
and the patient identification circuitry 410 includes biometric
analysis circuitry 426 configured to analyze the biometric signal
to determine the presence of the patient, and signal processing
circuitry 150 is configured to identify activity data corresponding
to an activity of the patient by identifying activity data
corresponding to a biometric signal indicative of a presence of the
patient.
[0144] In another aspect, identity signal 412 include includes at
least one authentication factor (e.g., one or more of a security
token, a password, a digital signature, and a cryptographic key),
and patient identification circuitry 410 includes authentication
circuitry 428.
[0145] In another aspect, identity signal 412 includes a device
identification code, which identifies unobtrusive
activity-detection system 108, a component thereof, or an
associated device. In an aspect, identity signal 412 includes a
cell phone identification code (e.g., an electronic serial number,
a mobile identification number, and a system identification code)
and patient identification circuitry 410 includes cell phone
identification circuitry 430. In some aspects, identity signal 412
includes a device identification code that identifies a computing
system or device, a stand-alone microprocessor-based system, or a
component thereof. A device identification code can serve to
identify a patient (e.g., patient 102 in FIG. 1 and FIG. 2)
providing the device thus identified is consistently used only by
the patient. Identifying the patient based on device identification
code may be done, for example, if some or all components of
unobtrusive activity-detection system 108 are shared by multiple
users but the device or component associated with the device
identification code is used consistently by the patient. In an
aspect, identity signal 412 includes an RFID signal, and patient
identification circuitry 410 includes RFID circuitry 432.
[0146] In an aspect, monitoring system 112 includes input device
436, which is used, for example, for receiving prescription
information 438 indicative of the treatment regimen prescribed to
the patient. In an aspect, input device 436 includes a user
interface device 440, for receiving information from a user (e.g.,
medical care provider 170). In another aspect, input device 436
includes a data input device 442, for receiving information from a
computing device or other electrical circuitry (e.g., like data
input device 214 described in connection with FIG. 2).
[0147] In an aspect, monitoring system 112 includes at least one
data storage device 450, which may be used, for example, for
storing prescription information 438 indicative of the treatment
regimen prescribed to the patient.
[0148] In various aspects, receiving device 136 includes, for
example, a wireless receiver 452, computer network connection 454,
communication port 456, or computer drive 458.
[0149] In an aspect, compliance determination circuitry 156
includes an activity analyzer 460 for analyzing activity data 128
to determine the non-speech activity pattern 120, and a comparator
462 for comparing the non-speech activity pattern 120 represented
by the activity data with the at least one characteristic activity
pattern 152. In some aspects, comparator 462 is configured to
compare the non-speech activity pattern 120 represented by activity
data 128 with a plurality of characteristic activity patterns 152,
484, and 486 (three are depicted in FIG. 4, but comparison can be
made with any number of characteristic activity patterns).
[0150] In another aspect, compliance determination circuitry 156
includes a comparator 462 for comparing the activity data 128 with
at least one characteristic activity data set 464 representing at
least one characteristic activity pattern 152. In an aspect,
comparator 462 is configured to compare activity data 128 with a
plurality of characteristic activity data sets 464, 480, and 482,
each said characteristic activity data set representing a
characteristic activity pattern (three are depicted in FIG. 4, but
comparison can be made with any number of characteristic activity
data sets). For example, in some aspects compliance determination
circuitry 156 is configured to determine whether the patient has
complied with the treatment regimen based upon a determination of
whether the received activity data signal 134 represents at least
one of a plurality of characteristic activity patterns 152.
[0151] In an aspect, compliance determination circuitry 156 is
configured to determine that the patient has failed to comply with
the treatment regimen. In another aspect, compliance determination
circuitry 156 is configured to determine that the patient has
complied with the treatment regimen.
[0152] In various aspects, reporting circuitry 160 includes a
display device 466, email generation circuitry 468 for generating
an email notification, wireless notification circuitry 470 for
transmitting a notification to a wireless device 472 (which may be,
for example, a cell phone used by medical care provider 170), audio
alarm circuitry 474 for generating an audio alarm, or data storage
circuitry 476 for storing a notification 478 in data storage device
450.
[0153] In an aspect, the at least one receiving device 136 is
adapted to receive a physiological activity data signal 382
indicative of at least one physiological signal sensed with at
least one physiological sensor operatively connected to the
unobtrusive activity-detection system at the patient location. In
an aspect, physiological activity data signal 382 is indicative of
whether the patient has complied with the treatment regimen. In
various aspects, physiological activity data signal 382 includes
one or more of EEG data (including, for example, an event-related
potential, wherein the event-related potential is related to
performance of the non-speech activity by the subject), heart rate
data, eye position data, or pupil diameter data.
[0154] FIGS. 5 and 6 provide brief, general descriptions of
environments in which embodiments may be implemented. FIG. 5
illustrates an example system that includes a thin computing device
520, which may be included in an electronic device that also
includes one or more device functional element 550. For example,
the electronic device may include any item having electrical or
electronic components playing a role in a functionality of the
item, such as a limited resource computing device, a wireless
communication device, a mobile wireless communication device, an
electronic pen, a handheld electronic writing device, a digital
camera, a scanner, an ultrasound device, an x-ray machine, a
non-invasive imaging device, a cell phone, a PDA, a Blackberry.RTM.
device, a printer, a refrigerator, a car, and an airplane. In
another example, the thin computing device may be included in a
medical apparatus or device. In a further example, the thin
computing device may be operable to communicate with a medical
apparatus.
[0155] The thin computing device 520 includes a processor 521, a
system memory 522, and a system bus 523 that couples various system
components including the system memory 522 to the processor 521.
The system bus 523 may be any of several types of bus structures
including a memory bus or memory controller, a peripheral bus, and
a local bus using any of a variety of bus architectures. In an
aspect, the system memory includes read-only memory (ROM) 524 and
random access memory (RAM) 525. A basic input/output system (BIOS)
526, containing the basic routines that help to transfer
information between sub-components within the thin computing device
520, such as during start-up, is stored in the ROM 524. A number of
program modules may be stored in the ROM 524 or RAM 525, including
an operating system 528, one or more application programs 529,
other program modules 530 and program data 531.
[0156] A user may enter commands and information into the computing
device 520 through input devices, such as a number of switches and
buttons, illustrated as hardware buttons 544, connected to the
system via a suitable hardware button interface 545. Input devices
may further include a touch-sensitive display with suitable input
detection circuitry, illustrated as a display 532 and screen input
detector 533. The output circuitry of the touch-sensitive display
532 is connected to the system bus 523 via a video driver 537.
Other input devices may include a microphone 534 connected through
a suitable audio interface 535, and a physical hardware keyboard
(not shown). Output devices may include at least one display 532
and at least one speaker 538.
[0157] In addition to the display 532, the computing device 520 may
include other peripheral output devices, such as a projector
display 536. Other external devices 539 may be connected to the
processor 521 through a USB port 540 and USB port interface 541, to
the system bus 523. Alternatively, the other external devices 539
may be connected by other interfaces, such as a parallel port, game
port or other port. External devices 539 include external input or
output devices, e.g., a joystick, game pad, satellite dish,
scanner, various types of sensors or actuators. Output signals
include device control signals. The computing device 520 may
further include or be capable of connecting to a flash card memory
(not shown) through an appropriate connection port (not shown). The
computing device 520 may further include or be capable of
connecting with a network through a network port 542 and network
interface 543, and through wireless port 546 and corresponding
wireless interface 547 may be provided to facilitate communication
with other peripheral devices, including other computers, printers,
and so on (not shown). It will be appreciated that the various
components and connections shown are examples and other components
and means of establishing communication links may be used.
[0158] The computing device 520 may be primarily designed to
include a user interface. The user interface may include a
character, a key-based, or another user data input via the touch
sensitive display 532. The user interface may include using a
stylus (not shown). Moreover, the user interface is not limited to
a touch-sensitive panel arranged for directly receiving input, but
may alternatively or in addition respond to another input device
such as the microphone 534. For example, spoken words may be
received at the microphone 534 and recognized. Alternatively, the
computing device 520 may be designed to include a user interface
having a physical keyboard (not shown).
[0159] The device functional elements 550 are typically application
specific and related to a function of the electronic device, and is
coupled with the system bus 523 through an interface (not shown).
The functional elements may typically perform a single well-defined
activity with little or no user configuration or setup, such as a
cell phone connecting with an appropriate tower and transceiving
voice or data information, or communicating with an implantable
medical apparatus, or a camera capturing and saving an image.
[0160] In certain instances, one or more elements of the thin
computing device 520 may be deemed not necessary and omitted. In
other instances, one or more other elements (e.g., other resources
552) may be deemed necessary and added to the thin computing
device.
[0161] FIG. 6 illustrates an example embodiment of a computing
system in which embodiments may be implemented, shown as a
computing system environment 600. Components of the computing
system environment 600 may include, but are not limited to, a
computing device 610 having a processor 620, a system memory 630,
and a system bus 621 that couples various system components
including the system memory to the processor 620. The system bus
621 may be any of several types of bus structures including a
memory bus or memory controller, a peripheral bus, and a local bus
using any of a variety of bus architectures. By way of example, and
not limitation, such architectures include Industry Standard
Architecture (ISA) bus, Micro Channel Architecture (MCA) bus,
Enhanced ISA (EISA) bus, Video Electronics Standards Association
(VESA) local bus, and Peripheral Component Interconnect (PCI) bus,
also known as Mezzanine bus.
[0162] The computing system environment 600 typically includes a
variety of computer-readable media products. Computer-readable
media may include any media that can be accessed by the computing
device 610 and include both volatile and non-volatile media,
removable and non-removable media. By way of example, and not of
limitation, computer-readable media may include computer storage
media. By way of further example, and not of limitation,
computer-readable media may include a communication media.
[0163] Computer storage media includes volatile and non-volatile,
removable and non-removable media implemented in any method or
technology for storage of information such as computer-readable
instructions, data structures, program modules, or other data.
Computer storage media includes, but is not limited to,
random-access memory (RAM), read-only memory (ROM), electrically
erasable programmable read-only memory (EEPROM), flash memory, or
other memory technology, CD-ROM, digital versatile disks (DVD), or
other optical disk storage, magnetic cassettes, magnetic tape,
magnetic disk storage, or other magnetic storage devices, or any
other medium which can be used to store the desired information and
which can be accessed by the computing device 610. In a further
embodiment, a computer storage media may include a group of
computer storage media devices. In another embodiment, a computer
storage media may include an information store. In another
embodiment, an information store may include a quantum memory, a
photonic quantum memory, or atomic quantum memory. Combinations of
any of the above may also be included within the scope of
computer-readable media.
[0164] Communication media may typically embody computer-readable
instructions, data structures, program modules, or other data in a
modulated data signal such as a carrier wave or other transport
mechanism and include any information delivery media. The term
"modulated data signal" means a signal that has one or more of its
characteristics set or changed in such a manner as to encode
information in the signal. By way of example, and not limitation,
communication media include wired media, such as a wired network
and a direct-wired connection, and wireless media such as acoustic,
RF, optical, and infrared media.
[0165] The system memory 630 includes computer storage media in the
form of volatile and non-volatile memory such as ROM 631 and RAM
632. A RAM may include at least one of a DRAM, an EDO DRAM, a
SDRAM, a RDRAM, a VRAM, or a DDR DRAM. A basic input/output system
(BIOS) 633, containing the basic routines that help to transfer
information between elements within the computing device 610, such
as during start-up, is typically stored in ROM 631. RAM 632
typically contains data and program modules that are immediately
accessible to or presently being operated on by processor 620. By
way of example, and not limitation, FIG. 6 illustrates an operating
system 634, application programs 635, other program modules 636,
and program data 637. Often, the operating system 634 offers
services to applications programs 635 by way of one or more
application programming interfaces (APIs) (not shown). Because the
operating system 634 incorporates these services, developers of
applications programs 635 need not redevelop code to use the
services. Examples of APIs provided by operating systems such as
Microsoft's "WINDOWS" are well known in the art.
[0166] The computing device 610 may also include other
removable/non-removable, volatile/non-volatile computer storage
media products. By way of example only, FIG. 6 illustrates a
non-removable non-volatile memory interface (hard disk interface)
640 that reads from and writes for example to non-removable,
non-volatile magnetic media. FIG. 6 also illustrates a removable
non-volatile memory interface 650 that, for example, is coupled to
a magnetic disk drive 651 that reads from and writes to a
removable, non-volatile magnetic disk 652, or is coupled to an
optical disk drive 655 that reads from and writes to a removable,
non-volatile optical disk 656, such as a CD ROM. Other
removable/nonremovable, volatile/non-volatile computer storage
media that can be used in the example operating environment
include, but are not limited to, magnetic tape cassettes, memory
cards, flash memory cards, DVDs, digital video tape, solid state
RAM, and solid state ROM. The hard disk drive 641 is typically
connected to the system bus 621 through a non-removable memory
interface, such as the interface 640, and magnetic disk drive 651
and optical disk drive 655 are typically connected to the system
bus 621 by a removable non-volatile memory interface, such as
interface 650.
[0167] The drives and their associated computer storage media
discussed above and illustrated in FIG. 6 provide storage of
computer-readable instructions, data structures, program modules,
and other data for the computing device 610. In FIG. 6, for
example, hard disk drive 641 is illustrated as storing an operating
system 644, application programs 645, other program modules 646,
and program data 647. Note that these components can either be the
same as or different from the operating system 634, application
programs 635, other program modules 636, and program data 637. The
operating system 644, application programs 645, other program
modules 646, and program data 647 are given different numbers here
to illustrate that, at a minimum, they are different copies.
[0168] A user may enter commands and information into the computing
device 610 through input devices such as a microphone 663, keyboard
62, and pointing device 661, commonly referred to as a mouse,
trackball, or touch pad. Other input devices (not shown) may
include at least one of a touch sensitive display, joystick, game
pad, satellite dish, and scanner. These and other input devices are
often connected to the processor 620 through a user interface 660
that is coupled to the system bus, but may be connected by other
interface and bus structures, such as a parallel port, game port,
or a universal serial bus (USB). Other devices that can be coupled
to the system bus via other interface and bus structures include
sensors of various types, for example.
[0169] A display 691, such as a monitor or other type of display
device or surface may be connected to the system bus 621 via an
interface, such as a video interface 690. A projector display
engine 692 that includes a projecting element may be coupled to the
system bus. In addition to the display, the computing device 610
may also include other peripheral output devices such as speakers
697 and printer 696, which may be connected through an output
peripheral interface 695. Outputs may be sent to a variety of other
types of devices, and are not limited to the example output devices
identified here.
[0170] The computing system environment 600 may operate in a
networked environment using logical connections to one or more
remote computers, such as a remote computer 680. The remote
computer 680 may be a personal computer, a server, a router, a
network PC, a peer device, or other common network node, and
typically includes many or all of the elements described above
relative to the computing device 610, although only a memory
storage device 681 has been illustrated in FIG. 6. The network
logical connections depicted in FIG. 6 include a local area network
(LAN) and a wide area network (WAN), and may also include other
networks such as a personal area network (PAN) (not shown). Such
networking environments are commonplace in offices, enterprise-wide
computer networks, intranets, and the Internet.
[0171] When used in a networking environment, the computing system
environment 600 is connected to the network 671 through a network
interface, such as the network interface 670, the modem 672, or the
wireless interface 693. The network may include a LAN network
environment, or a WAN network environment, such as the Internet. In
a networked environment, program modules depicted relative to the
computing device 610, or portions thereof, may be stored in a
remote memory storage device. By way of example, and not
limitation, FIG. 6 illustrates remote application programs 685 as
residing on computer medium 681. It will be appreciated that the
network connections shown are examples and other means of
establishing a communication link between the computers may be
used.
[0172] In certain instances, one or more elements of the computing
device 610 may be deemed not necessary and omitted. In other
instances, one or more other elements (e.g., other resources 625)
may be deemed necessary and added to the computing device.
[0173] FIGS. 5 and 6 illustrate generalized forms of
circuitry-based systems, in which systems as depicted in FIGS. 1-4
may be implemented. Although specific embodiments are described
herein, those skilled in the art will appreciate that methods and
systems as described herein can be implemented in various ways.
Reference is made herein to various circuitry systems/subsystems
(e.g., patient identification circuitry 222, activity detection
circuitry 122, notification circuitry 290 in FIG. 2, and patient
identification circuitry 410, reporting circuitry 160, and signal
processing circuitry 150 in FIG. 4) which may be considered to be
control/processing circuitry, and/or components thereof. In
general, control/processing circuitry (e.g., control/processing
circuitry 180 and control/processing circuitry 190 in FIG. 1)
includes any or all of digital and/or analog components, one or
more processor (e.g., a microprocessor), and includes memory and
additional components as described in connection with FIGS. 5 and
6.
[0174] In a general sense, those skilled in the art will recognize
that the various embodiments described herein can be implemented,
individually and/or collectively, by various types of electrical
circuitry having a wide range of electrical components such as
hardware, software, firmware, and/or virtually any combination
thereof. Electrical circuitry includes electrical circuitry having
at least one discrete electrical circuit, electrical circuitry
having at least one integrated circuit, electrical circuitry having
at least one application specific integrated circuit, electrical
circuitry forming a computing device configured by a computer
program (e.g., a computer configured by a computer program which at
least partially carries out processes and/or devices described
herein, or a microprocessor configured by a computer program which
at least partially carries out processes and/or devices described
herein), electrical circuitry forming a memory device, which may
include various types of memory (e.g., random access, flash, read
only, etc.), electrical circuitry forming a communications device
(e.g., a modem, communications switch, optical-electrical
equipment, etc.), and/or any non-electrical analog thereto, such as
optical or other analogs (e.g., graphene based circuitry). In an
embodiment, the system is integrated in such a manner that the
system operates as a unique system configured specifically for the
function of monitoring treatment compliance, and any associated
computing devices of the system operate as specific use computers
for purposes of the claimed system, and not general use computers.
In an embodiment, at least one of the associated computing devices
of the system is hardwired with a specific ROM to instruct the at
least one computing device. In a general sense, those skilled in
the art will recognize that the various aspects described herein
which can be implemented, individually and/or collectively, by a
wide range of hardware, software, firmware, and/or any combination
thereof can be viewed as being composed of various types of
"electrical circuitry."
[0175] At least a portion of the devices and/or processes described
herein can be integrated into a data processing system. A data
processing system generally includes one or more of a system unit
housing, a video display, memory such as volatile or non-volatile
memory, processors such as microprocessors or digital signal
processors, computational entities such as operating systems,
drivers, graphical user interfaces, and applications programs, one
or more interaction devices (e.g., a touch pad, a touch screen, an
antenna, etc.), and/or control systems including feedback loops and
control motors (e.g., feedback for sensing position and/or
velocity; control motors for moving and/or adjusting components
and/or quantities). A data processing system may be implemented
utilizing suitable commercially available components, such as those
typically found in data computing/communication and/or network
computing/communication systems.
[0176] As discussed in connection with FIG. 1, transmitting device
132 in unobtrusive activity-detection system 108 and receiving
device 136 in monitoring system 112 are configured to provide a
communication link between the two locations. In various aspects,
transmitting device 132 and receiving device 136 provide a wireless
communication link. A wireless communication link may also be
established between monitoring system 112 and wireless device 472,
as shown in FIG. 4. In various aspects, a wireless communication
link includes at least one of a radio frequency, wireless network,
cellular network, satellite, WiFi, BlueTooth, Wide Area Network
(WAN), Local Area Network (LAN), or Body Area Network (BAN)
communication link. Various types of communication links are
suitable for providing communication between two remote locations.
Communication between locations remote from each other may take
place over telecommunications networks, for example public or
private Wide Area Network (WAN). In general, communication between
remote locations is not considered to be suitably handled by
technologies geared towards physically localized networks, e.g.,
Local Area Network (LAN) technologies operation at Layer 1/2 (such
as the forms of Ethernet or WiFi). However, it will be appreciated
that portions (but not the entirety) of communication networks used
in remote communications may include technologies suitable for use
in physically localized network, such as Ethernet or WiFi. In an
aspect, system components are considered "remote" from each other
if they are not within the same room, building, or campus. In an
aspect, a remote system may include components separated by a few
miles or more. Conversely, system components may be considered
"local" to each other if they are located within the same room,
building, or campus.
[0177] FIG. 7 illustrates an embodiment of an unobtrusive
activity-detection system 700 that is based on a cell phone 702. In
this example, activity detection circuitry 122, activity analysis
circuitry 126, and transmitting device 132 are components of a cell
phone 702, formed from standard cell phone hardware configured with
application software. One or more touchscreen sensors 704, which
are used for receiving instructions for controlling phone 702
entered by patient 706, serve as activity sensors. One or more
activity signal 708 from touchscreen sensors 704 is processed by
touchscreen input processing application 710. Activity signal 708
represents the motion of the patient's finger on the touchscreen,
as sensed by touchscreen sensors 704. Touchscreen input processing
application 710 determines the timing of entry of instructions by
the patient. In an aspect, it is not necessary to determine the
specific instructions entered by the patient, but only to determine
how often the patient is using the phone, and/or how quickly the
patient is entering instructions into the phone. However, in other
aspects, the specific instructions can be detected, e.g., to
determine whether the patient is choosing to listen to music, play
a game, send or read email, receive a phone call, or place a phone
call. An EEG (electroencephalogram) sensor 712 serves as a
physiological sensor for providing further information relating to
the brain-related functioning of patient 706. EEG sensor 712
includes electrodes built into earbuds (which are used by the
patient 706 for listening to phone calls, music, or other audio
outputs provided by cell phone 702). Sensed EEG signal 714 is
processed by EEG processing application 722. Sensing of EEG signals
with sensors that fit into the ear canal is described, for example,
in U.S. Patent Publication 2003/0195588 to Fischell et al., and
U.S. Patent Publication 2006/0094974 to Cain, both of which are
incorporated herein by reference. See also Bleichner, et al.,
"Exploring Miniaturized EEG Electrodes for Brain-Computer
Interfaces. An EEG You Do Not See?" Physiological Reports 2015,
Vol. 3, Iss. 4, e12362, doi:10.14814/phy2.12363, which is
incorporated herein by reference. In an aspect, EEG sensor 712 is
used for detecting event-related potentials (ERPs) associated with
a detectable event associated with operation of cell phone 702. In
an aspect, the detectable event is an event that can be detected by
control/processing circuitry 180 in cell phone 702. For example, in
various aspects, the detectable event includes providing
notification of the arrival of an incoming call to patient 706
(e.g., by ringing or vibration of cell phone 702), providing
notification of the arrival of an email message or impending
calendared event with an audible tone or a pop-up message. As used
herein, a "detectable" event is an event that results in a
detectable change in control/processing circuitry 180 of cell phone
702. In principle, the "detectable" event is also expected to be
detectable by patient 706, at least at a sub-conscious level, with
such detection of the event by the patient resulting in generation
of an event-related potential that can be sensed with EEG sensor
712. Because changes in amplitude, latency, and/or topography of
event-related potentials have been observed in subjects with
various brain-related disorders (Hansenne, "Event-Related Brain
Potentials in Psychopathology: Clinical and Cognitive
Perspectives," Psychologica Belgica 2006, vol. 46, iss. 1-2, pp.
5-36, which is incorporated herein by reference), changes in
event-related potential production in response to a detectable
event, or absence of an event-related potential in response to a
detectable event provide information regarding the mental function
of the patient, and hence whether the patient has complied with a
prescribed treatment regimen. Motion sensor 714 in wristband 716
generates second activity signal 718 representing motion of patient
706. Second activity signal 718 is processed by motion processing
application 720. Activity detection circuitry 122 receives signals
724, 726, and 728 from touchscreen input processing application
710, motion processing application 720, and EEG processing
application 722, respectively, which are received by activity
detection circuitry 122 and processed to generate activity data
signal 134. Signal 724 from touchscreen input processing
application 710 supplies to activity detection circuitry
information regarding how often the patient 706 uses phone 702
(summarizing the patient's entry of instructions by category, e.g.,
by providing the number of times the person placed a phone call,
the number of times the patient looked at email, and the number of
hours per day spent listening to music). Signal 726 from motion
processing application 720 provides information regarding the
patient's activity level (sensed by motion sensor 714 in wristband
716), and signal 728 from EEG processing application 722 provides
information regarding how attentive the patient is to a the
detectable event (e.g., percent of the time that an ERP was
produced in response to a notification regarding the arrival of an
email). ERP information and activity patterns relating to patient
motion and touchscreen activity are processed in combination to
determine compliance of patient 706 with a prescribed treatment
regimen.
[0178] FIG. 8 depicts an embodiment of an unobtrusive
activity-detection system 800, implemented in a computing system
802. Computing system 802 includes computer 804, monitor 806,
keyboard 808, pointing device 810, and camera 812, which is built
into monitor 806 in the present example. Computing system 802 is
used by patient 814 to perform personal or work-related activities,
such as (for example, and without limitation) creating and editing
documents using word-processing software. In this example, keyboard
808 serves as an activity sensor, providing activity signal 816 to
activity detection circuitry 122. Other components of unobtrusive
activity-detection monitoring system 800 (e.g., activity analysis
circuitry 126, and transmitting device 132) are components of a
computing system 802. In addition, camera 812 provides an identify
signal (image signal 818) to patient identification circuitry 222,
where it is processed by facial recognition circuitry 238 in image
analysis circuitry 236 to determine the identity/presence of
patient 814 to generate presence signal 225. It will be appreciated
that it may also be possible to determine the identity/presence of
patient 814 by utilizing login/password information provided when
patient 814 logs onto computer 804 (or logs into a specific piece
of program or online accounts) for authentication. Activity signal
816 contains information regarding the patient's typing pattern,
which is analyzed by activity analysis circuitry 126, to generate
activity data signal 134, which is transmitted to a monitoring
location by transmitting device 132. Activity analysis circuitry
126 may analyze typing patterns using, for example, techniques as
described in U.S. Pat. No. 6,231,344 to Merzenich et al., U.S.
Published Patent Application 2005/0084832 to Janssen et al., each
of which is incorporated herein by reference
[0179] FIG. 9 depicts an embodiment of an unobtrusive
activity-detection system 900 that is implemented in connection
with a microwave oven 902. Microwave oven 902 is a "smart" oven
that includes a circuitry that allows it to send data to and
receive data from a computing network, for example, as described
in, e.g., U.S. Pat. No. 8,631,063 to Helal et al., U.S. Pat. No.
9,113,795 to Hong et al., U.S. Pat. No. 8,667,112 to Roth et al.,
each of which is incorporated herein by reference. Microwave oven
902 includes control/processing circuitry 180 and communication
circuitry (including transmitting device 132), allowing it to
connect to the computer network 904 via a wireless router 906 or
other wireless communication device (e.g., a cell phone or laptop
computer). Activity detection circuitry 122, activity analysis
circuitry 126, and transmitting device 132 are components of
microwave oven 902. Keypad 908 of microwave oven 902 is used as an
activity sensor, providing an activity signal 912 to activity
detection circuitry 122. When patient 910 uses keypad 908 to
operate microwave oven 902, activity signal 912 is sent to activity
detection circuitry 122. In an aspect, the pattern of use of
microwave oven, as indicated by activation of keypad 908 (e.g.,
time of day that it is used, frequency of use during the day) may
be indicative of the brain-related functioning of the patient. For
example, a depressed patient may be less likely to make the effort
to prepare food, and will use the microwave oven less than usual.
In other cases the patient may use the microwave more often than is
typical for that patient, or at unusual times of the day or night.
A patient that is showing symptoms of dementia may have difficulty
pressing the keys on the keypad in the appropriate sequence in
order to heat food. Accordingly, accuracy of operation of the
microwave oven (e.g., whether the patient presses keys in the
proper sequence to select cooking time and temperature and turns on
the oven, and how many attempts it takes to operate the oven
properly) may be indicative of the patient's alertness or
coordination. Identity of patient 910 is determined by sensing an
RFID signal from RFID device 914, using RFID sensor 916. Identity
signal 918 from RFID sensor 916 is provided to patient identity
circuitry 222, which generates presence signal 225, as discussed
herein above. It is contemplated that RFID device 914 is a passive
RFID device, but in other embodiments an active RFID could be used.
RFID device 914 is depicted as taking the form of a wristband worn
by patient 910, but it could be embodied in a necklace, a key fob,
an implant, clothing, or other form. As an alternative, patient 910
could be identified by sensing an identification signal from a cell
phone or smart watch carried by patient 910.
[0180] FIG. 10 depicts an example of an unobtrusive
activity-detection system 1000 that is incorporated into a game
system 1002. Game system 1002 includes a game console 1004, game
controller 1006 for providing control signals to game console 1004,
and display 1008 driven by video output from game console 1004.
Game controller 1006 functions as an activity sensor; as patient
1010 plays the game, signals from game controller 1006 are used as
activity signal 1012, which is processed by activity detection
circuitry 122 and activity analysis circuitry 126 in game console
1004. Sensing and processing of game controller signals, e.g., to
determine reaction times, may be substantially as described in U.S.
Pat. No. 5,913,310 to Brown, or U.S. Pat. No. 6,186,145 to Brown,
both of which are incorporated herein by reference. It will be
appreciated that while Brown describes a video game designed
primarily for health care-related teaching purposes, the video game
may be for entertainment purposes, and need not include an
educational or medical component. Activity detection circuitry 122
and activity analysis circuitry 126 include special-purpose
hardware and/or software incorporated into game console 1004 (in
the form of an add-on card or software). Username/password
information entered into game controller 1006 by patient 1010 is
used as an authentication signal 1014 processed by authentication
circuitry 246 in patient identification circuitry 222 to generate
presence signal 225 that indicates presence of the patient. Game
console 1004 also includes transmitting device 132, which is used
for communicating with network 1020, including transmitting
activity data signal 134 to a monitoring location for processing as
described elsewhere herein.
[0181] FIG. 11 depicts an example of an unobtrusive
activity-detection system 1100 that is incorporated into a vehicle
system 1102. Vehicle system 1102 includes one or more components of
vehicle 1104, which are built into vehicle 1104 during manufacture
or subsequently installed in vehicle 1104. Vehicle system
components include vehicle controls 1106 (including, but not
limited to ignition 1108, brakes 1110, steering 1112, lights 1114,
accelerator 1116, or door locks 1118) and auxiliary systems 1120
(including, but not limited to, location sensing 1122, dashboard
camera 1124, event recorder or "black box" 1126 used for tracking
vehicle acceleration, deceleration, etc., entertainment system
1128, or communication system 1130). Communication system 1130 may
include, for example, a telephone or radio system. The presence
and/or identity of patient 1140 in vehicle 1104 is sensed by RFID
sensor 1142, which detects RFID 1144 in key fob 1146 carried by
patient 1140. Activity of patient 1140 is sensed by one or more
vehicle system sensor 1150, including one or more sensors
associated with vehicle controls 1106 or auxiliary systems 1120. A
wide variety of types of patient activity can be sensed by vehicle
system sensor 1150 to provide information regarding the patient's
brain-related function. For example, in various aspects patient
activity sensed by vehicle system sensor 1150 includes, but is not
limited to acceleration, deceleration or steering of vehicle 1104,
choice of music, activation/deactivation of lights or door locks,
coordination (determined through analysis of video from dashboard
cam), choice of location as assessed by location sensing (e.g.,
GPS) system, etc. In various aspects, rate, frequency, and
consistency of sensor activation provide information regarding the
patient's mental state. Activity signal 1152 from vehicle system
sensor 1150 is provided to activity detection circuitry 122 and
activity analysis circuitry 126, which are components of vehicle
system 1102, and activity data signal 134 from activity detection
circuitry 122 is transmitted by transmitting device 132, which is
also a component of a vehicle system 1102.
[0182] FIG. 12 depicts an example of an unobtrusive
activity-detection system 1200 in which activity detection
circuitry 122, activity analysis circuitry 126, and transmitting
device 132 for transmitting activity data signal 134 to a
monitoring location are components of a kiosk 1202 (e.g., as
described generally in U.S. Pat. No. 9,135,403 to Tolmosoff, and
U.S. Pat. No. 8,996,392 to Cashman et al., both of which are
incorporated herein by reference). Kiosk 1202 is a medical kiosk
used to provide health-related information, perform medical
monitoring (e.g., take a blood pressure reading), dispense
medication, and the like. Kiosk 1202 includes a touchscreen 1204,
camera 1206, and prescription dispenser 1208. Operation of kiosk
1202 is controlled by control/processing circuitry 180. Patient
1220 signs in to a personal healthcare account via kiosk 1202 by
entering a login name and password via touchscreen 1204, by
scanning an identification card, or by some other authentication
method. Inputs from touchscreen 1204 are processed by touchscreen
input tracking 1224. Authentication signal 1212 from touchscreen
1204 (or alternatively, from a card scanner) is provided to
authentication circuitry 246 in patient identification circuitry
222. After signing into a personal healthcare account via kiosk
1202, patient 1220 is able to pick up a prescription via
prescription dispenser 1208, or perform other healthcare-related
activities. While patient 1220 interacts with kiosk 1202 via
touchscreen 1204, camera 1206 captures an image of the patient's
face, which is provided to control/processing circuitry 180 as a
first activity signal 1214. Eye movement has been shown to be
indicative of brain-related state, and eye tracking circuitry 1222
is used to track the patient's eye position/direction of gaze and
determine the patient's eye movement pattern to assess
brain-related state, for example using an approach as described in
U.S. Pat. No. 8,808,195 to Tseng et al., which is incorporated
herein by reference.
[0183] In an aspect, camera 1206 is a smart camera which captures
images of the eyes of patient 1202. Image data may include results
of visual spectrum imaging, infrared imaging, ultrasound imaging.
Smart cameras are commercially available (e.g., Hamamatsu's
Intelligent Vision System;
http://jp.hamamatsu.com/en/product_info/index.html). Such image
capture systems may include dedicated processing elements for each
pixel image sensor. Other possible camera systems may include, for
example, a pair of infrared charge coupled device cameras to
continuously monitor pupil diameter and position. This can be done
as the eye follows a moving visual target, and can provide
real-time data relating to pupil accommodation relative to objects
on a display (e.g.,
http://jp.hamamatsu.com/en/rd/publication/scientific_american/common/pdf/-
scientific_06 08.pdf).
[0184] Eye movement and/or pupil movement may also be measured by
video-based eye tracking circuitry. In these systems, a camera 1206
built into kiosk 1202 focuses on one or both eyes and records eye
movement as the viewer looks at a stimulus. Contrast may be used to
locate the center of the pupil, and infrared and near-infrared
non-collimated light may be used to create a corneal reflection.
The vector between these two features can be used to compute gaze
intersection with a surface after a calibration for a subject.
[0185] Two types of eye tracking techniques include bright pupil
eye tracking and dark pupil eye tracking Their difference is based
on the location of the illumination source with respect to the
optical system. If the illumination is coaxial with the optical
path, then the eye acts as a retroreflector as the light reflects
off the retina, creating a bright pupil effect similar to red eye.
If the illumination source is offset from the optical path, then
the pupil appears dark. Thus, in some embodiments, the gaze
tracking stimulus source and the gaze response signal sensor are
co-aligned. Alternatively, the gaze tracking stimulus source and
the gaze response signal sensor may be separately aligned and
located.
[0186] Bright Pupil tracking creates greater iris/pupil contrast
allowing for more robust eye tracking that is less dependent upon
iris pigmentation and greatly reduces interference caused by
eyelashes and other obscuring features. It also allows for tracking
in lighting conditions ranging from total darkness to very bright
light. However, bright pupil techniques are not recommended for
tracking outdoors as extraneous infrared (IR) sources may interfere
with monitoring.
[0187] Most eye tracking systems use a sampling rate of at least 30
Hz. Although 50/60 Hz is most common, many video-based eye tracking
systems run at 240, 350 or even 1000/1250 Hz, which is recommended
in order to capture the detail of the very rapid eye movements
during reading, for example.
[0188] Eye movements are typically divided into fixations, when the
eye gaze pauses in a certain position, and saccades, when the eye
gaze moves to another position. A series of fixations and saccades
is called a scanpath. Most information from the eye is made
available during a fixation, not during a saccade. The central one
or two degrees of the visual angle (the fovea) provide the bulk of
visual information; input from larger eccentricities (the
periphery) generally is less informative. Therefore the locations
of fixations along a scanpath indicate what information loci on the
stimulus were processed during an eye tracking session. On average,
fixations last for around 200 milliseconds during the reading of
linguistic text, and 350 milliseconds during the viewing of a
scene. Preparing a saccade towards a new goal takes around 200
milliseconds. Scanpaths are useful for analyzing cognitive intent,
interest, and salience. Other biological factors (some as simple as
gender) may affect the scanpath as well. Eye tracking in
human-computer interaction typically investigates the scanpath for
usability purposes, or as a method of input in gaze-contingent
displays, also known as gaze-based interfaces.
[0189] Commercial eye tracking software packages can analyze eye
tracking and show the relative probability of eye fixation at
particular locations. This allows for a broad analysis of which
locations received attention and which ones were ignored. Other
behaviors such as blinks, saccades, and cognitive engagement can be
reported by commercial software packages. A gaze tracking system
for monitoring eye position is available from Seeing Machines Inc.,
Tucson, Ariz. (see e.g., the Specification Sheet: "faceLAB.TM. 5
Specifications" which is incorporated herein by reference). Eye
position, eye rotation, eye gaze position against screen, pupil
diameter and eye vergence distance may be monitored. Eye rotation
measurements of up to +/-45 degrees around the y-axis and +/-22
degrees around the x-axis are possible. Typical static accuracy of
gaze direction measurement is 0.5-1 degree rotational error.
[0190] In addition, in some aspects an image obtained with camera
1206 can be used to determine movement or coordination of the
patient. In an aspect, control/processing circuitry 180 includes
image processing hardware and/or software used to determine an
activity or posture of the subject from an image obtained from
camera 1206. Such image processing hardware and/or software may,
for example, include or generate a model of the background of the
image, segment the image, identify the subject in the image, and
analyze the image to determine activity or posture of the subject,
e.g., based on parameters such as the angle of the torso relative
to the hips, or angle of the shoulders relative to the hips.
Processing of an image to determine position or posture-related
information may be, for example, as described in U.S. Pat. No.
7,616,779 issued Nov. 10, 2009 to Liau et al., U.S. Pat. No.
8,396,283, issued Mar. 12, 2013 to Iihoshi et al., U.S. Pat. No.
7,330,566, issued Feb. 12, 2008 to Cutler, or U.S. Pat. No.
7,728,839 issued Jun. 1, 2010 to Yang et al., each of which is
incorporated herein by reference. In addition, the signal from
touchscreen 1204, representing entry of data and instructions via
touchscreen 1204 by patient 1220 is used as a second activity
signal 1216. Rate, timing, type, and consistency of data entry as
assessed through analysis of second activity signal 1216 also
provide information regarding the patient's brain-related state.
Activity Analysis circuitry 126 combines information from activity
signal 1214 and activity signal 1216 to determine compliance of
patient 1220 with a prescribed treatment regimen.
[0191] FIG. 13 depicts an example of an unobtrusive
activity-detection system 1300 that is incorporated into an
intercommunication ("intercom") system 1302, for example, of the
type used with an access control system to control entry of
individuals to an apartment building or office building. In an
aspect, intercommunication system 1302 includes master station 1304
and at least one remote station 1306. In an aspect, remote station
1306 is an example of a system 108 depicted in FIG. 2, and master
station 1304 is an example of a system 112, as depicted in FIG. 4.
Master station 1304 is used, for example, at a monitoring location
114 such as the reception desk of the building, where it is
monitored by a member of the building staff, for example. Remote
station 1306 is used at an entrance to a building to grant access
to regular occupants or visitors to the building. This location is
considered to be patient location 110 in the situation that remote
station 1306 is used to control access of the patient to the
building. Remote station 1306 includes keypad 1310, camera 1312,
microphone 1314, and speaker 1316. In order to request access to
the building, the patient typically presses one or more buttons on
keypad 1310. An image of the patient is detected with camera 1312;
the patient's voice is sensed with microphone 1314 and speaker 1316
provides for delivery of recorded messages, other notification
sounds, or verbal instructions from a building staff person at
master station 1304. Master station 1304 includes display 1320 for
displaying an image of the patient, speaker 1322 for presenting a
voice signal detected with microphone 1314, keypad 1324, and
handset 1326 which includes a microphone for sensing a voice signal
from the building staff person at master station 1304 to deliver to
the patient via speaker 1316. The pattern of entry of an access
code, detected via keypad 1310, serves as activity signal 118.
Camera 1312 detects an image of the iris of the patient, which
serves as identity signal 1330 (i.e., camera 1312 serves as a
biometric sensor). Detection of patient presence/identity through
biometric analysis can be performed by any of the various
approaches described herein above. Activity signal 118 and identity
signal 1330 are processed by control/processing circuitry 180,
activity detection circuitry 122, activity analysis circuitry 126
to generate activity data 128. Transceiver 1332 transmits activity
data signal 1334 to transceiver 1336 in monitoring system 1308. In
addition, transceiver 1332 transmits image signal 1338 from camera
1312 and voice signal 1340 from microphone 1314, and receives voice
signal 1342, sensed via handset 1326, from master station 1304.
Activity data signal 1334 is processed by control/processing
circuitry 190, and signal processing circuitry 150, compliance
determination circuitry 156 and reporting circuitry 160 as
described in connection with FIGS. 1 and 4. Additional data signals
and instructions relating to operation of intercommunication system
1302 are sent between remote station 1306 and master station 1304
via transceivers 1332 and 1336, respectively, but are not depicted
in FIG. 13.
[0192] FIG. 14 depicts an example of an unobtrusive
activity-detection system 1400 that includes a motion sensor 1402
built into (or, alternatively, attached to) a hair brush 1404 used
by patient 1406. In an aspect, motion sensor 1402 is a tri-axial
accelerometer. Motion associated with the use of hair brush 1404 is
sensed with motion sensor 1402, and an activity signal 1408 is
transmitted to personal computing device 1410. (Here, personal
computing device 1410 is a tablet computer, but it could
alternatively be a cell phone, laptop computer, desktop computer,
for example.) Personal computing device 1410 includes
control/processing circuitry 180, including activity detection
circuitry 122, activity analysis circuitry 126, and transmitting
device 132. Application software 1412 configures hardware of
personal computing device 1410 to perform functions of activity
detection circuitry 122 and activity analysis circuitry 126.
Transmitting device 132 transmits activity data signal 134 to
monitoring system 1414 via network 1416. In an aspect, activity
data signal 134 includes information regarding the time of day at
which hair brush 1404 was used and how long it was used for. In
many cases, this will provide sufficient information regarding use
of hair brush 1404 by patient 1406. However, information relating
to the nature of movement sensed--e.g., was the movement weak or
vigorous, erratic or regular, was any tremor detected, etc. may
also be sensed and may provide additional information regarding the
brain-related functioning of patient 1406. In another aspect,
motion sensor 1402 or other activity sensor, activity detection
circuitry 122, activity analysis circuitry 126, and transmitting
device 132 are all components of a personal item such as hair brush
1404.
[0193] FIG. 15 is a flow diagram of a method 1500 relating to
monitoring compliance of a patient with a prescribed treatment
regimen. Method 1500 includes sensing with at least one activity
sensor in an unobtrusive activity-detection system at least one
activity signal including a non-speech activity pattern
corresponding to performance of a non-speech activity by a patient
at a patient location, the patient having a brain-related disorder
and a prescribed treatment regimen for treating at least one aspect
of the brain-related disorder, as indicated at 1502; processing the
at least one activity signal with activity detection circuitry in
the unobtrusive activity-detection system to identify at least one
section of the at least one activity signal containing the
non-speech activity pattern, as indicated at 1504; analyzing the at
least one section of the at least one activity signal with activity
analysis circuitry in the unobtrusive activity-detection system to
generate activity data including data indicative of whether the
patient has complied with the treatment regimen, as indicated at
1506; and transmitting an activity data signal including the
activity data including data indicative of whether the patient has
complied with the treatment regimen to a receiving device at a
monitoring location with at least one transmitting device at the
patient location, as indicated at 1508. In various aspects, method
1500 is carried out with unobtrusive activity detection system 108
as depicted in FIGS. 1, 2 and 3, for example.
[0194] FIGS. 16-28 depict variations and expansions of method 1500
as shown in FIG. 15. In the methods depicted in FIGS. 16-28, steps
1502-1508 are as described generally in connection with FIG. 15.
Here and elsewhere, method steps outlined with dashed lines
represent steps that are included in some, but not all method
aspects, and combinations of steps other than those specifically
depicted in the figures are possible as would be known by those
having ordinary skill in the relevant art.
[0195] FIG. 16 depicts method 1600, which includes steps 1502-1508
as described above. As indicated at 1602, in an aspect the
non-speech activity pattern corresponds to unprompted performance
of the non-speech activity by the patient. As indicated at 1604, in
another aspect, the non-speech activity pattern corresponds to
performance of the non-speech activity by the patient in connection
with an activity of daily life. Examples of "activities of daily
life" are listed herein above.
[0196] In an aspect, method 1600 includes receiving with an input
device a treatment signal indicative of initiation of treatment of
the patient according to the treatment regimen and beginning to
sense the at least one activity signal responsive to receipt of the
treatment signal indicative of initiation of treatment of the
patient, as indicated at 1606. See, e.g., treatment signal 220 in
FIG. 2.
[0197] FIG. 17 depicts method 1700, which includes steps 1502-1508
as described in connection with FIG. 15. In an aspect, method 1700
includes performing at least one of sensing the at least one
activity signal, processing the at least one activity signal,
analyzing the at least one section of the at least one activity
signal, and transmitting the activity data substantially
continuously, as indicated at 1702. In another aspect, method 1700
includes performing at least one of sensing the at least one
activity signal, processing the at least one activity signal,
analyzing the at least one section of the at least one activity
signal, and transmitting the activity data intermittently, as
indicated at 1704. In another aspect, method 1700 includes
performing at least one of sensing the at least one activity
signal, processing the at least one activity signal, analyzing the
at least one section of the at least one activity signal, and
transmitting the activity data according to a schedule, as
indicated at 1706.
[0198] FIG. 18 depicts method 1800, wherein sensing the at least
one activity signal includes sensing at least one activity signal
including an activity pattern corresponding to performance of a
motor activity, as indicated at 1802. In various aspects, the motor
activity includes typing, as indicated at 1804; providing an input
via a user interface device, as indicated at 1806; providing an
input via a touchscreen, as indicated at 1808; providing an input
via a pointing device, as indicated at 1810; controlling a game
system, as indicated at 1812; controlling a vehicle system, as
indicated at 1814; or walking, as indicated at 1816.
[0199] FIG. 19 depicts a method 1900,wherein sensing the at least
one activity signal includes sensing at least one activity signal
including an activity pattern corresponding to performance of an
activity of daily life, as indicated at 1902. In various aspects,
the activity of daily life includes at least one of hygiene, as
indicated at 1904; eating, as indicated at 1906; dressing, as
indicated at 1908; performing a grooming activity, as indicated at
1910 (e.g., brushing hair, as indicated at 1912; brushing teeth, as
indicated at 1914; or combing hair, as indicated at 1916);
preparing food, as indicated at 1918; interacting with another
person, as indicated at 1920; interacting with an animal, as
indicated at 1922; interacting with a machine, as indicated at
1924; interacting with an electronic device, as indicated at 1926;
or using an implement, as indicated at 1928.
[0200] FIG. 20 depicts a method 2000, wherein, in various aspects,
sensing the at least one activity signal includes sensing at least
one signal from a pressure sensor, as indicated at 2002; a force
sensor, as indicated at 2004; a capacitive sensor, as indicated at
2006; an imaging device, as indicated at 2008; a motion sensor, as
indicated at 2010; an acceleration sensor, as indicated at 2012; or
an optical sensor, as indicated at 2014.
[0201] FIG. 21 depicts a method 2100, which includes sensing at
least one physiological signal with at least one physiological
sensor operatively connected to the unobtrusive activity-detection
system, as indicated at 2102. For example, in an aspect the at
least one physiological signal is indicative of whether the patient
has complied with the treatment regimen, as indicated at 2104. In
an aspect, the at least one physiological signal includes an EEG
signal, as indicated at 2106. For example, in an aspect the at
least one physiological signal includes an event-related potential,
wherein the event-related potential is related to performance of
the non-speech activity by the subject, as indicated at 2108. In
other aspects, the at least one physiological signal includes one
or more of a heart signal, as indicated at 1220; an eye position
signal, as indicated at 2112; or a pupil diameter signal, as
indicated at 2114.
[0202] FIG. 22 depicts a method 2200, which includes determining a
presence of the patient with patient identification circuitry based
on at least one identity signal sensed at the patient location,
wherein sensing with the at least one activity sensor in the
unobtrusive activity-detection system the at least one activity
signal including the non-speech activity pattern corresponding to
performance of the non-speech activity by the patient at the
patient location includes sensing an activity of the patient based
at least in part on the determination of the presence of the
patient by the patient identification circuitry, as indicated 2202.
In an aspect, the identity signal includes at least a portion of
the at least one activity signal, and determining the presence of
the patient with patient identification circuitry based on the at
least one identity signal includes determining that at least a
portion of the at least one activity signal matches a known
activity pattern of the patient, as indicated at 2204. In another
aspect, the identity signal includes a voice signal received from
an audio sensor at the patient location, and determining the
presence of the patient from the at least one identity signal
includes analyzing the voice signal to determine the presence of
the patient, and wherein processing the at least one activity
signal with activity detection circuitry to identify the at least
one section of the at least one activity signal containing the
non-speech activity pattern includes identifying at least a portion
of the activity signal containing activity corresponding to the
voice signal indicative of the presence of the patient, as
indicated at 2206.
[0203] In another aspect, as indicated at 2208, the identity signal
includes a biometric signal from at least one biometric sensor at
the patient location, wherein determining the presence of the
patient from the at least one identity signal includes analyzing
the biometric signal to determine the presence of the patient, and
wherein processing the at least one activity signal with activity
detection circuitry to identify at least one section of the at
least one activity signal containing the non-speech activity
pattern includes identifying at least a portion of the activity
signal containing activity corresponding to a biometric signal
indicative of the presence of the patient.
[0204] FIG. 23 is a flow diagram showing further aspects of the
method shown in FIG. 22. Method 2300, shown in FIG. 23, includes
step 1502-1508, as described herein above, as well as step 2202,
which is described in connection with FIG. 22. In addition, in
method 2300, the identity signal includes an image signal received
from an imaging device at the patient location, wherein determining
the presence of the patient from the at least one identity signal
includes analyzing the image signal to determine the presence of
the patient, and wherein processing the at least one activity
signal with activity detection circuitry to identify at least one
section of the at least one activity signal containing the
non-speech activity pattern includes identifying at least a portion
of the activity signal containing activity corresponding to an
image signal indicative of the presence of the patient, as
indicated at 2302. Method 2300 includes analyzing the image signal
to determine the presence of the patient through facial
recognition, as indicated at 2304, or analyzing the image signal to
determine the presence of the patient through gait or posture
recognition, as indicated at 2306.
[0205] In other aspects, the identity signal includes at least one
authentication factor, as indicated at 2308 (for example, a
security token, a password, a digital signature, or a cryptographic
key, as indicated at 2310), or a cell phone identification code, as
indicated at 2312 (for example, an electronic serial number, a
mobile identification number, or system identification code, as
indicated at 2314). In yet other aspects, the identity signal
includes an RFID signal, as indicated at 2316.
[0206] FIG. 24 depicts further aspects of a method 2400 relating to
sensing of the activity signal. For example, in various aspects,
the at least one activity signal includes a signal from a keyboard,
as indicated at 2402; a signal from a pointing device, as indicated
at 2404; a signal from a user interface device, as indicated at
2406; a signal from a touchscreen, as indicated at 2408; a signal
from a remote controller for an entertainment device or system, as
indicated at 2410; a signal from a camera, as indicated at 2412; a
signal from at least one pressure sensor, as indicated at 2414; a
signal from at least one force sensor, as indicated at 2416; a
signal from at least one capacitive sensor, as indicated at 2418; a
signal from at least one imaging device, as indicated at 2420; a
signal from at least one optical sensor, as indicated at 2422; a
signal from at least one motion sensor, as indicated at 2424; a
signal from at least one acceleration sensor, as indicated at 2426;
or a signal from at least one game controller, as indicated at
2428.
[0207] FIG. 25 shows various other method aspects. For example, in
an aspect, a method 2500 includes receiving at least one
instruction from the monitoring location, as indicated at 2502;
receiving a signal representing the prescribed treatment regimen
from the monitoring location, as indicated at 2504; storing the at
least one activity signal in a data storage device, as indicated at
2506; storing the activity data in a data storage device, as
indicated at 2508; or transmitting time data to the receiving
device with the at least one transmitting device at the patient
location, the time data indicative of the time at which the at
least one section of the at least one activity signal was detected,
as indicated at 2510. In an aspect, transmitting the activity data
signal to the receiving device at the monitoring location includes
transmitting a wireless signal, as indicated at 2512. In another
aspect, transmitting the activity data signal to the receiving
device at the monitoring location includes transmitting a signal
via a computer network connection, as indicated at 2514.
[0208] FIG. 26 depicts a method 2600. In an aspect, method 2600
includes processing the at least one activity signal to exclude at
least one portion of the at least one activity signal that does not
contain activity of the patient, as indicated at 2602. In another
aspect, method 2600 includes processing the at least one section of
the at least one activity signal to determine at least one activity
pattern of the patient, as indicated at 2604. In an aspect, the
activity data includes the at least one activity pattern of the
patient, as indicated at 2606. For example, in an aspect method
2600 includes determining at least one activity parameter
indicative of whether the patient has complied with the treatment
regimen, wherein the activity data includes the at least one
activity parameter, as indicated at 2608.
[0209] In some aspects, method 2600 includes comparing the at least
one activity pattern with at least one characteristic activity
pattern to determine whether the patient has complied with the
treatment regimen, as indicated at 2610. For example, in an aspect
comparing the at least one activity pattern with at least one
characteristic activity pattern to determine whether the patient
has complied with the treatment regimen includes comparing the at
least one activity pattern with at least one previous activity
pattern of the patient to determine whether the patient has
complied with the treatment regimen, as indicated at 2612. For
example, in various aspects, the at least one previous activity
pattern is representative of an activity pattern of the patient
prior to initiation of treatment of the brain-related disorder, as
indicated at 2614; an activity pattern of the patient after
initiation of treatment of the brain-related disorder, as indicated
at 2616; an activity pattern of the patient during known compliance
of the patient with a treatment of the brain-related disorder, as
indicated at 2618; and an activity pattern of the patient during
treatment with a specified treatment regimen, as indicated at
2620.
[0210] FIG. 27 depicts aspects of a method 2700, showing further
aspects of step 2604 as shown in FIG. 26. In an aspect, method 2700
includes comparing the at least one activity pattern with a
plurality of activity patterns, and determining which of the
plurality of activity patterns best matches the at least one
activity pattern, as indicated at 2702. In an aspect, the plurality
of activity patterns are stored prior activity patterns of the
patient, and the prior activity patterns are representative of
activity patterns of the patient with different treatment regimens,
as indicated at 2704. In another aspect, the plurality of activity
patterns are stored population activity patterns representative of
activity patterns of populations of subjects, as indicated at 2706.
For example, in various aspects, at least one of the population
activity patterns is representative of activity patterns of a
population of subjects without the brain-related disorder, as
indicated at 2708; activity patterns of a population of untreated
subjects with the brain-related disorder, as indicated at 2710;
activity patterns of a population of subjects having the
brain-related disorder stabilized by treatment, as indicated at
2712; or activity patterns of a population of subjects undergoing
different treatment regimens for the brain-related disorder, as
indicated at 2714.
[0211] FIG. 28 depicts a method 2800. In various aspects, the
brain-related disorder is an emotional disorder, as indicated at
2802; a personality disorder, as indicated at 2804; a mental
disorder, as indicated at 2806; a traumatic brain injury-related
disorder, as indicated at 2808; Parkinson's disease, as indicated
at 2810; an Autism Spectrum Disorder, as indicated at 2812;
Alzheimer's disease, as indicated at 2814; Bipolar Disorder, as
indicated at 2816; depression, as indicated at 2828; schizophrenia,
as indicated at 2820; a psychological disorder, as indicated at
2822; or a psychiatric disorder, as indicated at 2824.
[0212] As noted above, in some aspects, a brain-related disorder is
a mental disorder, psychological disorder, or psychiatric disorder.
A mental disorder, psychological disorder, or psychiatric disorder
can include, for example, a psychological pathology,
psychopathology, psychosocial pathology, social pathology, or
psychobiology disorder. A mental disorder, psychological disorder,
or psychiatric disorder can be any disorder categorized in any
Diagnostic and Statistical Manual (DSM) or International
Statistical Classification of Diseases (ICD) Classification of
Mental and Behavioural Disorders text, and may be, for example and
without limitation, a neurodevelopmental disorder (e.g., autism
spectrum disorder or attention-deficit/hyperactivity disorder), a
psychotic disorder (e.g., schizophrenia), a mood disorder, a
bipolar disorder, a depressive disorder, an anxiety disorder, an
obsessive-compulsive disorder, a trauma-or stressor-related
disorder, a dissociative disorder, a somatic symptom disorder, an
eating disorder, an impulse-control disorder, a substance-related
or addictive disorder, a personality disorder (e.g., narcissistic
personality disorder or antisocial personality disorder), a
neurocognitive disorder, a major or mild neurocognitive disorder
(e.g., one due to Alzheimer's disease, traumatic brain injury, HIV
infection, prion disease, Parkinson's disease, Huntington's
disease, or substance/medication). A mental disorder, psychological
disorder, or psychiatric disorder can be any disorder described by
the NIH National Institute of Mental Health (NIMH) Research Domain
Criteria Project and may include a biological disorder involving
brain circuits that implicate specific domains of cognition,
emotion, or behavior. In an aspect, a brain-related disorder
includes a serious mental illness or serious emotional
disturbance.
[0213] In various aspects, a brain-related disorder includes a
serious mental illness or serious emotional disturbance, a mental
disorder, psychological disorder, or psychiatric disorder.
[0214] In an aspect, a brain disorder is a traumatic disorder, such
as a traumatic brain injury. Traumatic brain injury-induced
disorders may present with dysfunction in cognition, communication,
behavior, depression, anxiety, personality changes, aggression,
acting out, or social inappropriateness. See, e.g., Jeffrey Nicholl
and W. Curt LaFrance, Jr., "Neuropsychiatric Sequelae of Traumatic
Brain Injury," Semin Neurol. 2009, 29(3):247-255.
[0215] In an aspect, a brain-related disorder is a lesion-related
disorder. A brain lesion can include, for example and without
limitation, a tumor, an aneurysm, ischemic damage (e.g., from
stroke), an abscess, a malformation, inflammation, or any damage
due to trauma, disease, or infection. An example of a
lesion-related disorder is a disorder associated with a
right-hemisphere lesion.
[0216] In an aspect, a brain disorder is a neurological disorder. A
neurological disorder may be, for example and without limitation,
Alzheimer's disease, a brain tumor, a developmental disorder,
epilepsy, a neurogenetic disorder, Parkinson's disease,
Huntington's disease, a neurodegenerative disorder, stroke,
traumatic brain injury or a neurological consequence of AIDS.
Neurological disorders are described on the website of the National
Institutes of Health (NIH) National Institute of Neurological
Disorders and Stroke (NINDS).
[0217] In various embodiments, methods as described herein may be
performed according to instructions implementable in hardware,
software, and/or firmware. Such instructions may be stored in
non-transitory machine-readable data storage media, for example.
Those having skill in the art will recognize that the state of the
art has progressed to the point where there is little distinction
left between hardware, software, and/or firmware implementations of
aspects of systems; the use of hardware, software, and/or firmware
is generally (but not always, in that in certain contexts the
choice between hardware and software can become significant) a
design choice representing cost vs. efficiency tradeoffs. Those
having skill in the art will appreciate that there are various
vehicles by which processes and/or systems and/or other
technologies described herein can be effected (e.g., hardware,
software, and/or firmware), and that the preferred vehicle will
vary with the context in which the processes and/or systems and/or
other technologies are deployed. For example, if an implementer
determines that speed and accuracy are paramount, the implementer
may opt for a mainly hardware and/or firmware vehicle;
alternatively, if flexibility is paramount, the implementer may opt
for a mainly software implementation; or, yet again alternatively,
the implementer may opt for some combination of hardware, software,
and/or firmware in one or more machines, compositions of matter,
and articles of manufacture. Hence, there are several possible
vehicles by which the processes and/or devices and/or other
technologies described herein may be effected, none of which is
inherently superior to the other in that any vehicle to be utilized
is a choice dependent upon the context in which the vehicle will be
deployed and the specific concerns (e.g., speed, flexibility, or
predictability) of the implementer, any of which may vary. Those
skilled in the art will recognize that optical aspects of
implementations will typically employ optically oriented hardware,
software, and or firmware.
[0218] In some implementations described herein, logic and similar
implementations may include software or other control structures.
Electrical circuitry, for example, may have one or more paths of
electrical current constructed and arranged to implement various
functions as described herein. In some implementations, one or more
media may be configured to bear a device-detectable implementation
when such media hold or transmit device detectable instructions
operable to perform as described herein. In some variants, for
example, implementations may include an update or modification of
existing software or firmware, or of gate arrays or programmable
hardware, such as by performing a reception of or a transmission of
one or more instructions in relation to one or more operations
described herein. Alternatively or additionally, in some variants,
an implementation may include special-purpose hardware, software,
firmware components, and/or general-purpose components executing or
otherwise invoking special-purpose components.
[0219] Implementations may include executing a special-purpose
instruction sequence or invoking circuitry for enabling,
triggering, coordinating, requesting, or otherwise causing one or
more occurrences of virtually any functional operations described
herein. In some variants, operational or other logical descriptions
herein may be expressed as source code and compiled or otherwise
invoked as an executable instruction sequence. In some contexts,
for example, implementations may be provided, in whole or in part,
by source code, such as C++, or other code sequences. In other
implementations, source or other code implementation, using
commercially available and/or techniques in the art, may be
compiled/implemented/translated/converted into a high-level
descriptor language (e.g., initially implementing described
technologies in C or C++ programming language and thereafter
converting the programming language implementation into a
logic-synthesizable language implementation, a hardware description
language implementation, a hardware design simulation
implementation, and/or other such similar mode(s) of expression).
For example, some or all of a logical expression (e.g., computer
programming language implementation) may be manifested as a
Verilog-type hardware description (e.g., via Hardware Description
Language (HDL) and/or Very High Speed Integrated Circuit Hardware
Descriptor Language (VHDL)) or other circuitry model which may then
be used to create a physical implementation having hardware (e.g.,
an Application Specific Integrated Circuit). Those skilled in the
art will recognize how to obtain, configure, and optimize suitable
transmission or computational elements, material supplies,
actuators, or other structures in light of these teachings.
[0220] This detailed description sets forth various embodiments of
devices and/or processes via the use of block diagrams, flowcharts,
and/or examples. Insofar as such block diagrams, flowcharts, and/or
examples contain one or more functions and/or operations, it will
be understood by those within the art that each function and/or
operation within such block diagrams, flowcharts, or examples can
be implemented, individually and/or collectively, by a wide range
of hardware, software, firmware, or virtually any combination
thereof. In an embodiment, several portions of the subject matter
described herein may be implemented via Application Specific
Integrated Circuits (ASICs), Field Programmable Gate Arrays
(FPGAs), digital signal processors (DSPs), or other integrated
formats. However, those skilled in the art will recognize that some
aspects of the embodiments disclosed herein, in whole or in part,
can be equivalently implemented in integrated circuits, as one or
more computer programs running on one or more computers (e.g., as
one or more programs running on one or more computer systems), as
one or more programs running on one or more processors (e.g., as
one or more programs running on one or more microprocessors), as
firmware, or as virtually any combination thereof, and that
designing the circuitry and/or writing the code for the software
and or firmware would be well within the skill of one having skill
in the art in light of this disclosure. In addition, those skilled
in the art will appreciate that the mechanisms of the subject
matter described herein are capable of being distributed as a
program product in a variety of forms, and that an illustrative
embodiment of the subject matter described herein applies
regardless of the particular type of signal bearing medium used to
actually carry out the distribution. Examples of a signal bearing
medium include, but are not limited to non-transitory
machine-readable data storage media such as a recordable type
medium such as a floppy disk, a hard disk drive, a Compact Disc
(CD), a Digital Video Disk (DVD), a digital tape, a computer
memory, etc. A signal bearing medium may also include transmission
type medium such as a digital and/or an analog communication medium
(e.g., a fiber optic cable, a waveguide, a wired communications
link, a wireless communication link (e.g., transmitter, receiver,
transmission logic, reception logic, etc.) and so forth).
[0221] FIG. 29 is a block diagram of a computer program product
2900 for implementing a method as described in connection with FIG.
15. Computer program product 2900 includes a signal-bearing medium
2902 bearing one or more instructions for sensing with at least one
activity sensor in an unobtrusive activity-detection system at
least one activity signal including a non-speech activity pattern
corresponding to performance of a non-speech activity by a patient
at a patient location, the patient having a brain-related disorder
and a prescribed treatment regimen for treating at least one aspect
of the brain-related disorder; one or more instructions for
processing the at least one activity signal with activity detection
circuitry in the unobtrusive activity-detection system to identify
at least one section of the at least one activity signal containing
the non-speech activity pattern; one or more instructions for
analyzing the at least one section of the at least one activity
signal with activity analysis circuitry in the unobtrusive
activity-detection system to generate activity data including data
indicative of whether the patient has complied with the treatment
regimen; and one or more instructions for transmitting an activity
data signal including the activity data including data indicative
of whether the patient has complied with the treatment regimen to a
receiving device at a monitoring location with at least one
transmitting device at the patient location, as indicated at 2904.
Signal-bearing medium 2902 may be, for example, a computer-readable
medium 2906, a recordable medium 2908, a non-transitory
signal-bearing medium 2910, or a communications medium 2912,
examples of which are described herein above.
[0222] FIG. 30 is a block diagram of a system 3000 for implementing
a method as described in connection with FIG. 15. System 3000
includes a computing device 3002 and instructions that when
executed on the computing device cause the computing device to
control the sensing with at least one activity sensor in an
unobtrusive activity-detection system of at least one activity
signal including a non-speech activity pattern corresponding to
performance of a non-speech activity by a patient at a patient
location, the patient having a brain-related disorder and a
prescribed treatment regimen for treating at least one aspect of
the brain-related disorder; process the at least one activity
signal with activity detection circuitry in the unobtrusive
activity-detection system to identify at least one section of the
at least one activity signal containing the non-speech activity
pattern; analyze the at least one section of the at least one
activity signal with activity analysis circuitry in the unobtrusive
activity-detection system to generate activity data including data
indicative of whether the patient has complied with the treatment
regimen; and control the transmitting an activity data signal
including the activity data including data indicative of whether
the patient has complied with the treatment regimen to a receiving
device at a monitoring location with at least one transmitting
device at the patient location, as indicated at 3004. System 3000
may be, for example, a cell phone configured with application
software 3006, a computing system or device 3008, or a
microprocessor-based system 3010 or various other systems as
described herein. Furthermore, the system may include sensors,
input devices, and output devices, e.g., as depicted FIGS. 2, 5,
and 7 for example.
[0223] FIG. 31 is a flow diagram of a method 3100 relating to
monitoring compliance of a patient with a prescribed treatment
regimen. Method 3100 includes receiving an activity data signal
with a receiving device at a monitoring location, the activity data
signal transmitted to the monitoring location from a patient
location, the activity data signal containing activity data
representing at least one non-speech activity pattern in activity
sensed from a patient with at least one activity sensor in an
unobtrusive activity-detection system at the patient location
during performance of the non-speech activity by the patient, the
patient having a brain-related disorder and a prescribed treatment
regimen intended to treat at least one aspect of the brain-related
disorder, as indicated at 3102; analyzing the activity data signal
with signal processing circuitry at the monitoring location to
determine whether the activity data represents at least one
non-speech activity pattern that matches at least one
characteristic activity pattern, as indicated at 3104; determining
with compliance determination circuitry at the monitoring location
whether the patient has complied with the prescribed treatment
regimen based on whether the activity data represents the at least
one non-speech activity pattern that matches the at least one
characteristic activity pattern, as indicated at 3106; and
reporting with reporting circuitry a conclusion based on the
determination of whether the patient has complied with the
prescribed treatment regimen, as indicated at 3108. In various
aspects, method 3100 is carried out with monitoring system 118 as
depicted in FIGS. 1 and 4, for example.
[0224] FIGS. 32-48 depict variations and expansions of method 3100
as shown in FIG. 31. In the methods depicted in FIGS. 32-48, steps
3102-3108 are as described generally in connection with FIG. 31.
Here and elsewhere, method steps outlined with dashed lines
represent steps that are included in some, but not all method
aspects, and combinations of steps other than those specifically
depicted in the figures are possible as would be known by those
having ordinary skill in the relevant art.
[0225] FIG. 32 depicts a method 3200, wherein the non-speech
activity pattern corresponds to unprompted performance of the
non-speech activity by the patient, as indicated at 3202. In an
aspect, method 3200 includes receiving a signal indicative of
initiation of treatment of the patient according to the treatment
regimen and beginning to receive activity data with the receiving
device responsive to receipt of the signal indicative of initiation
of treatment of the patient, as indicated at 3204.
[0226] FIG. 33 depicts a method 3300. In an aspect, method 3300
includes performing substantially continuously at least one of
receiving the activity data signal with the receiving device,
analyzing the activity data signal with the signal processing
circuitry, determining with the compliance determining circuitry
whether the patient has complied with the prescribed treatment
regimen, and reporting the conclusion with the reporting circuitry,
as indicated at 3302. In another aspect, method 3300 includes
performing intermittently at least one of receiving the activity
data signal with the receiving device, analyzing the activity data
signal with the signal processing circuitry, determining with the
compliance determining circuitry whether the patient has complied
with the prescribed treatment regimen, and reporting the conclusion
with the reporting circuitry, as indicated at 3304. In another
aspect, method 3300 includes performing according to a schedule at
least one of receiving the activity data signal with the receiving
device, analyzing the activity data signal with the signal
processing circuitry, determining with the compliance determining
circuitry whether the patient has complied with the prescribed
treatment regimen, and reporting the conclusion with the reporting
circuitry, as indicated at 3306.
[0227] Aspects of a method 3400 are shown in FIG. 34. In one
aspect, the activity data represents a non-speech activity pattern
corresponding to performance of a motor activity, as indicated at
3402, which in various aspects includes typing, as indicated at
3404; providing input via a user interface device, as indicated at
3406; or walking, as indicated at 3408.
[0228] In another aspect, the activity data represents a non-speech
activity pattern corresponding to performance of an activity of
daily life, as indicated at 3410. For example, in various aspects
the activity of daily life includes at least one of hygiene,
washing, eating, dressing, brushing hair, combing hair, preparing
food, interacting with another person, interacting with an animal,
interacting with a machine, interacting with an electronic device,
or using an implement, as indicated at 3412.
[0229] Further aspects relating to receipt of the activity data
signal are shown in method 3500 depicted in FIG. 35. In various
aspects, the activity data signal contains activity data indicative
of a keystroke pattern, as indicated at 3502; activity data
indicative of an activity performance pattern, as indicated at
3530; activity data indicative of an activity performance rate, as
indicated at 3504; activity data indicative of an activity
performance time, as indicated at 3506; activity data indicative of
an activity performance frequency, as indicated at 3508; activity
data indicative of an activity performance variability, as
indicated at 3510; activity data indicative of an activity
performance accuracy, as indicated at 3512; activity data
indicative of an activity performance error rate, as indicated at
3514; activity data including data from a pressure sensor, as
indicated at 3516; activity data including data from a force
sensor, as indicated at 3518; activity data including data from a
capacitive sensor, as indicated at 3520; activity data including
data from an imaging device, as indicated at 3522; activity data
including data from a motion sensor, as indicated at 3524; activity
data including data from an acceleration sensor, as indicated at
3526; and activity data including data from an optical sensor, as
indicated at 3528.
[0230] FIG. 36 depicts aspects of a method 3600, which includes
receiving with at least one receiving device a physiological
activity data signal indicative of at least one physiological
signal sensed with at least one physiological sensor operatively
connected to the unobtrusive activity-detection system, as
indicated at 3602. In an aspect, the at least one physiological
activity data signal is indicative of whether the patient has
complied with the treatment regimen, as indicated at 3604. In
various aspects, the at least one physiological activity data
signal includes EEG data, as indicated at 3606; an event-related
potential, wherein the event-related potential is related to
performance of the non-speech activity by the subject, as indicated
at 3608; heart rate data, as indicated at 3610; eye position data,
as indicated at 3612; or pupil diameter data, as indicated at
3614.
[0231] FIG. 37 depicts aspect of method 3700, which includes
determining a presence of the patient with patient identification
circuitry at the monitoring location from at least one identity
signal received at the monitoring location from the patient
location, and using activity identification circuitry to identify
patient activity data corresponding to activity of the patient
based at least in part on the identity signal, as indicated at
3702. In an aspect, the identity signal includes at least a portion
of the activity data signal, and wherein determining the presence
of the patient with the patient identification circuitry at the
monitoring location from the at least one identity signal includes
analyzing activity data in the activity data signal to identify at
least a portion of the activity data that matches a known activity
pattern of the patient, as indicated at 3704. In an aspect, the
identity signal includes a voice signal, wherein determining the
presence of the patient with the patient identification circuitry
at the monitoring location from the at least one identity signal
includes analyzing the voice signal to determine the presence of
the patient, and wherein using activity identification circuitry to
identify patient activity data corresponding to activity of the
patient based at least in part on the identity signal includes
identifying activity data corresponding to a voice signal
indicative of a presence of the patient, as indicated at 3706. In
an aspect, the identity signal includes an image signal received
from an imaging device at the patient location, wherein determining
the presence of the patient with the patient identification
circuitry at the monitoring location from the at least one identity
signal includes analyzing the image signal to determine the
presence of the patient, and wherein using activity identification
circuitry to identify patient activity data corresponding to
activity of the patient based at least in part on the identity
signal includes identifying activity data corresponding to an image
signal indicative of a presence of the patient, as indicated at
3708. For example, in an aspect, analyzing the image signal to
determine the presence of the patient includes determining the
presence of the patient through facial recognition, as indicated at
3710. In another aspect, analyzing the image signal to determine
the presence of the patient includes determining the presence of
the patient through gait or posture recognition, as indicated at
3712.
[0232] FIG. 38 depicts a method 3800, showing further aspects
relating to determination of the presence of the patient with
patient identification circuitry at 3702, which is as described in
connection with FIG. 37. As indicated at 3802, in an aspect the
identity signal includes a biometric signal from at least one
biometric sensor at the patient location, wherein determining the
presence of the patient with the patient identification circuitry
at the monitoring location from the at least one identity signal
includes analyzing the voice signal to determine the presence of
the patient, and wherein using activity identification circuitry to
identify patient activity data corresponding to activity of the
patient based at least in part on the identity signal includes
identifying activity data corresponding to a biometric signal
indicative of a presence of the patient.
[0233] In another aspect, the identity signal includes at least one
authentication factor, as indicated at 3804. For example, in
various aspects the authentication factor is selected from the
group consisting of a security token, a password, a digital
signature, and a cryptographic key, as indicated at 3806. In
another aspect, the identity signal includes a cell phone
identification code, as indicated at 3808, for example, an
electronic serial number, a mobile identification number, and a
system identification code, as indicated at 3810. In another
aspect, the identity signal includes an RFID signal, as indicated
at 3812. In yet another aspect, method 3800 includes separating
patient activity data from the patient from activity data from
other people, as indicated at 3814.
[0234] FIG. 39 depicts method 3900, which includes, in various
aspects, receiving time data with a receiving device, the time data
transmitted to the monitoring location from the patient location,
the time data indicative of a time at which the activity data
representing the at least one non-speech activity pattern was
sensed, as indicated at 3902; storing prescription information in a
data storage device at the monitoring location, the prescription
information representing the prescribed treatment regimen, as
indicated at 3904; receiving prescription information representing
the prescribed treatment regimen, as indicated at 3906; prescribing
the treatment regimen intended to treat the at least one aspect of
the brain-related disorder to the patient, as indicated at
3908.
[0235] FIG. 40 depicts a method 4000, which includes determining a
time at which the activity data representing the at least one
non-speech activity pattern that matches the at least one
characteristic activity pattern was detected from the patient,
wherein the at least one characteristic activity pattern
corresponds to an activity pattern expected to be produced in the
subject in response to the prescribed treatment regimen at a
specific time following initiation of the prescribed treatment
regimen, as indicated 4002.
[0236] FIG. 41 depicts method 4100 illustrating further aspects
relating to receiving an activity data signal at 3102. In various
aspects of method 4100, receiving the activity data signal includes
at least one of receiving a wireless signal, as indicated at 4102;
receiving data via a computer network connection, as indicated at
4104; receiving data from a communication port, as indicated at
4106; and receiving data from a data storage device, as indicated
at 4108.
[0237] FIG. 42 depicts method 4200, illustrating further aspects
relating to analyzing the activity data signal at 3104. In an
aspect, analyzing the activity data signal with signal processing
circuitry at the monitoring location to determine whether the
activity data represents at least one non-speech activity pattern
that matches at least one characteristic activity pattern includes
comparing the non-speech activity pattern represented by the
activity data with the at least one characteristic activity
pattern, as indicated at 4202. In an aspect, comparing the
non-speech activity pattern represented by the activity data with
the at least one characteristic activity pattern includes comparing
the non-speech activity pattern represented by the activity data
with a plurality of characteristic activity patterns, as indicated
at 4204. In connection therewith, method 4200 includes determining
which of the plurality of characteristic activity patterns best
matches the non-speech activity pattern represented by the activity
data, as indicated at 4206. For example, in an aspect method 4200
includes determining a treatment regimen corresponding to the
characteristic activity pattern that best matches the non-speech
activity pattern, wherein the plurality of characteristic activity
patterns include a plurality of previous non-speech activity
patterns each representative of a non-speech activity pattern of
the patient undergoing a different treatment regimen for treatment
of the brain-related disorder, as indicated at 4208. In another
aspect, method 4200 includes determining a treatment regimen
corresponding to the characteristic activity pattern that best
matches the non-speech activity pattern, wherein the plurality of
characteristic activity patterns include a plurality of population
non-speech activity patterns each representative of a typical
non-speech activity pattern for a population of subjects undergoing
a different treatment regimen for treatment of the brain-related
disorder, as indicated at 4210.
[0238] FIG. 43 depicts a method 4300, wherein analyzing the
activity data signal with signal processing circuitry at the
monitoring location to determine whether the activity data
represents at least one non-speech activity pattern that matches at
least one characteristic activity pattern includes comparing the
activity data with characteristic activity data representing the
characteristic activity pattern, as indicated at 4302. In an
aspect, comparing the activity data with the characteristic
activity data representing the characteristic activity pattern
includes comparing the activity data with a plurality of
characteristic activity data sets, each said characteristic
activity data set representing a characteristic activity pattern,
as indicated at 4304. The method may also include determining which
of the plurality of characteristic activity data sets best matches
the activity data, as indicated at 4306. In an aspect, each said
characteristic activity data set corresponds to a stored non-speech
activity pattern representative of the patient undergoing a
distinct treatment regimen, as indicated at 4308. In an aspect,
each said characteristic activity data set corresponds to a stored
non-speech activity pattern representative of a population of
subjects undergoing a distinct treatment regimen, as indicated at
4310. The method may include determining a treatment regimen
associated with the characteristic activity data set that best
matches the activity data, as indicated at 4312.
[0239] FIG. 44 depicts aspects of a method 4400 relating to
reporting with reporting circuitry a conclusion based on the
determination of whether the patient has complied with the
prescribed treatment regimen, as shown at 3108. In an aspect,
reporting a conclusion based on the determination of whether the
patient has complied with the treatment regimen includes displaying
a report on a display device, as indicated at 4402.
[0240] In another aspect, reporting a conclusion based on the
determination of whether the patient has complied with the
treatment regimen includes generating a notification, as indicated
at 4404. In other aspects, reporting a conclusion based on the
determination of whether the patient has complied with the
treatment regimen includes one or more of transmitting a
notification to a wireless device, as indicated at 4406; generating
an audio alarm, as indicated at 4408; or storing a notification in
a data storage device, as indicated at 4410.
[0241] FIG. 45 depicts method 4500, showing method aspects relating
to determining whether the patient has complied with the prescribed
treatment regimen, at 3106. In an aspect, determining with the
compliance determination circuitry whether the patient has complied
with the treatment regimen includes determining that the patient
has failed to comply with the prescribed treatment regimen, as
indicated at 4502. In another aspect, wherein determining with the
compliance determination circuitry whether the patient has complied
with the treatment regimen includes determining that the patient
has complied with the prescribed treatment regimen, as indicated at
4504. In another aspect, determining with the compliance
determination circuitry whether the patient has complied with the
treatment regimen includes determining a degree of compliance of
the patient with the prescribed treatment regimen, as indicated at
4506.
[0242] FIG. 46 depicts a method 4600, in which, in various aspects,
the brain-related disorder is an emotional disorder, as indicated
at 4602; a personality disorder, as indicated at 4604; a mental
disorder, as indicated at 4606; a traumatic brain injury-related
disorder, as indicated at 4608; schizophrenia, as indicated at
4610; Parkinson's disease, as indicated at 4612; an Autism Spectrum
Disorder, as indicated at 4614; Alzheimer's disease, as indicated
at 4616; Biopolar Disorder, as indicated at 4618; depression, as
indicated at 4620; a psychological disorder, as indicated at 4622;
or a psychiatric disorder, as indicated at 4624.
[0243] FIG. 47 depicts a method 4700, wherein the at least one
characteristic activity pattern includes at least one previous
non-speech activity pattern of the patient, as indicated at 4702.
In various aspects, the at least one previous non-speech activity
pattern is representative of a non-speech activity pattern of the
patient prior to initiation of treatment of the brain-related
disorder, as indicated at 4704; a non-speech activity pattern of
the patient after initiation of treatment of the brain-related
disorder, as indicated at 4706; a non-speech activity pattern of
the patient during known compliance of the patient with a treatment
of the brain-related disorder, as indicated at 4708; or a
non-speech activity pattern of the patient during treatment with a
specified treatment regimen, as indicated at 4710.
[0244] FIG. 48 depicts a method 4800, wherein the at least one
characteristic activity pattern includes at least one population
activity pattern representative of a typical non-speech activity
pattern of a population of subjects, as indicated at 4802. In
various aspects, the at least one population activity pattern is
representative of non-speech activity patterns of a population
without the brain-related disorder, as indicated at 4804; an
untreated population with the brain-related disorder, as indicated
at 4806; or a population having the brain-related disorder
stabilized by a treatment regimen, as indicated at 4808.
[0245] FIG. 49 is a block diagram of a computer program product
4900 for implementing a method as described in connection with FIG.
31. Computer program product 4900 includes a signal-bearing medium
4902 bearing one or more instructions for receiving an activity
data signal with a receiving device at a monitoring location, the
activity data signal transmitted to the monitoring location from a
patient location, the activity data signal containing activity data
representing at least one non-speech activity pattern in activity
sensed from a patient with at least one activity sensor in an
unobtrusive activity-detection system at the patient location
during performance of the non-speech activity by the patient, the
patient having a brain-related disorder and a prescribed treatment
regimen intended to treat at least one aspect of the brain-related
disorder, one or more instructions for analyzing the activity data
signal with signal processing circuitry at the monitoring location
to determine whether the activity data represents at least one
non-speech activity pattern that matches at least one
characteristic activity pattern, one or more instructions for
determining with compliance determination circuitry at the
monitoring location whether the patient has complied with the
prescribed treatment regimen based on whether the activity data
represents the at least one non-speech activity pattern that
matches the at least one characteristic activity pattern, and one
or more instructions for reporting with reporting circuitry a
conclusion based on the determination of whether the patient has
complied with the prescribed treatment regimen, as indicated at
4904. Signal-bearing medium 4902 may be, for example, a
computer-readable medium 4906, a recordable medium 4908, a
non-transitory signal-bearing medium 4910, or a communications
medium 4912, examples of which are described herein above.
[0246] FIG. 50 is a block diagram of a system 5000 for implementing
a method as described in connection with FIG. 31. System 5000
includes a computing device 5002 and instructions that when
executed on the computing device cause the computing device to
control the receiving of an activity data signal with a receiving
device at a monitoring location, the activity data signal
transmitted to the monitoring location from a patient location, the
activity data signal containing activity data representing at least
one non-speech activity pattern in activity sensed from a patient
with at least one activity sensor in an unobtrusive
activity-detection system at the patient location during
performance of the non-speech activity by the patient, the patient
having a brain-related disorder and a prescribed treatment regimen
intended to treat at least one aspect of the brain-related
disorder; analyze the activity data signal with signal processing
circuitry at the monitoring location to determine whether the
activity data represents at least one non-speech activity pattern
that matches at least one characteristic activity pattern;
determine with compliance determination circuitry at the monitoring
location whether the patient has complied with the prescribed
treatment regimen based on whether the activity data represents the
at least one non-speech activity pattern that matches the at least
one characteristic activity pattern; and control the reporting with
reporting circuitry of a conclusion based on the determination of
whether the patient has complied with the prescribed treatment
regimen, as indicated at 5004. System 5000 may be, for example, a
cell phone configured with application software 5006, a computing
system or device 5008, or a microprocessor-based system 5010.
[0247] In other aspects, systems may be constructed which utilizes
two or more activity signals detected from the patient in order to
determine whether the patient has complied with a prescribed
treatment regimen. Such systems may utilize various combinations of
activity signals as described herein, or utilize one or more
activity signals as described herein in combination with an audio
signal including speech from the patient. Information regarding
compliance with a treatment regimen can be based in part upon
analysis of patient speech.
[0248] FIG. 51 is a block diagram of a system 5100 for monitoring
compliance of a patient with a treatment regimen based upon two or
more sensed signals. System 5100 includes communication system 5102
at patient location 5104 and monitoring system 5106 at monitoring
location 5108. In general, communication system 5102 includes
components shown in unobtrusive activity detection system 108 in
FIG. 2, as well as any additional components required for perform
communication system functions. Communication system 5102 includes
at least one audio sensor 5110 for sensing at least one audio
signal 5112, which includes patient speech from patient 102 at a
patient location 5104 during use of communication system 5102. In
an aspect, communication system 5102 includes a telephone (e.g., as
depicted in FIG. 7), an intercommunication system (e.g., as
depicted in FIG. 13), or a radio communication system, and audio
sensor is a microphone or other audio sensing device as known by
those of ordinary skill in the art. Patient 102 has a brain-related
disorder and a prescribed treatment regimen 104 for treating at
least one aspect of the brain-related disorder. Communication
system 5102 includes at least one first activity sensor 5120 for
sensing at least one first activity signal 5122 indicative of a
first activity of the patient. Communication system 5102 includes
signal processing circuitry 5124, which is configured to process
the at least one first activity signal 5122 and at least one second
activity signal 5126, which indicative of a second activity of the
patient, to generate at least one activity data signal 5130, the
activity data signal 5130 containing activity data 5132 indicative
of whether the patient has complied with the treatment regimen.
Communication system 5102 also includes at least one transmitting
device 5134 at the patient location for transmitting the at least
one activity data signal 5130 and at least one audio data signal
5136 based on the at least one audio signal 5112 to a receiving
device 5138 at monitoring location 5108. In an aspect, activity
signal 5126 includes audio signal 5112 from audio sensor 5110,
which can supply information regarding speech or vocal activity of
patient 102. In an aspect, signal processing circuitry 5124
includes speech processor 5128. In an aspect, speech processor 5128
is configured to process the at least one audio signal 5112 to
identify at least one portion of the at least one audio signal 5112
containing spontaneous speech of the patient. In an aspect, speech
processor 5128 is configured to process at least one audio signal
5112 to exclude at least one portion of at least one audio signal
5112 that does not contain spontaneous speech of the patient. In an
aspect, activity data 5132 includes the at least one section of the
at least one audio signal 5112 containing spontaneous speech of the
patient.
[0249] In an aspect, speech processor 5128 is configured to process
at least one audio signal 5112 to determine at least one speech
pattern of the patient. In an aspect, activity data 5132 includes
the at least one speech pattern. A speech pattern can be defined as
a consistent, characteristic form, style, or method of speech
comprising a distribution or arrangement of repeated or
corresponding parts composed of qualities, acts, or tendencies. In
an embodiment a speech pattern can include one or more qualities of
diction, elocution, inflection, and/or intonation. In an embodiment
a speech pattern can include aspects of language at the lexical
level, sentential level, or discourse level. In an embodiment, a
speech pattern may conform to the Thought, Language, and
Communication Scale and/or Thought and Language Index. Reviews
describing speech patterns and linguistic levels and the tools used
to study them include Covington M. A., et al. "Schizophrenia and
the structure of language: The linguist's view," Schizophrenia
Research 77: 85-98, 2005, and Kuperberg and Caplan (2003 Book
Chapter: Language Dysfunction in Schizophrenia), which are both
incorporated herein by reference.
[0250] In an embodiment, a speech pattern includes a linguistic
pattern determined at the lexical level. A speech pattern may
include a frequency of, for example, pauses, words, or phrases. For
example, a speech pattern may include a frequency of pauses. A
higher frequency of pauses or reduced verbal fluency can be
indicative of alogia associated with a brain disorder, e.g.,
bipolar disorder, depression, or schizophrenia. For example, a
speech pattern may include a frequency of dysfluencies ("uhs" and
"ums"). A higher than average frequency of dysfluencies may
indicate a slowed speech, the inability to think clearly, or a
deliberate attempt to appear unaffected by illness, all of which
have been associated with psychological pathologies. For example, a
speech pattern may include a distribution of pauses and
dysfluencies. A high frequency and particular distribution of
pauses and dysfluencies may be indicative of anomia associated with
schizophrenia or with an aphasia due to brain injury. For example,
a speech pattern may include a frequency of neologisms and/or word
approximations, or glossomania. Higher than average frequencies of
neologisms and/or word approximations, or glossomania, have been
associated with disorders such as schizophrenia, schizoaffective
disorder, or mania. For example, a speech pattern may include a
frequency of word production. A frequency of word production lower
than the norm may be indicative of a brain disorder such as
schizophrenia. An excessive speed during speech, as in pressured
speech, may be indicative of a brain disorder such as the mania of
bipolar disorder, while reduced speed may be indicative of
depression or a depressive episode. For example, a pattern may
include a type:token ratio (i.e., number of different words (types)
in relation to the total number of words spoken (tokens)). A
type:token ratio that is generally lower than the norm can be
indicative of schizophrenia. For example, a speech pattern may
include a frequency of specific words. Quantitative word counts
have been used as a tool in the identification and examination of
abnormal psychological processes including major depression,
paranoia, and somatization disorder. A high frequency of negative
emotion words or death-related words may be indicative of
depression. Psychologically relevant words can include those listed
in one or more dictionaries of the Linguistic Inquiry and Word
Count (LIWC) program (see Tausczik and Pennebaker, "The
Psychological Meaning of Words: LIWC and Computerized Text Analysis
Methods," Journal of Language and Social Psychology 29(1): 24-54,
2010, which is incorporated herein by reference). Words interpreted
as carrying normative emotional qualities are found in dictionaries
of two programs, Affective Norms for English Words (ANEW) and
Dictionary of Affect in Language (DAL)(see Whissell C., "A
comparison of two lists providing emotional norms for English words
(ANEW and the DAL)," Psychol Rep., 102(2):597-600, 2008, which is
incorporated herein by reference).
[0251] In an embodiment, a speech pattern includes a linguistic
pattern determined at the sentential level or discourse level. For
example, a speech pattern can include a consistent grammatical
style. A pattern comprising a style that is grammatically deviant
from the norm might include the overuse of the past tense,
indicating detachment from the subject being discussed. A pattern
comprising a style that is grammatically deviant from the norm,
e.g., as reflected by a higher percentage of simple sentences and,
in compound sentences, fewer dependent clauses may be indicative of
schizophrenia. For example, a speech pattern may include a ratio of
syntactic complexity (number of clauses and proportion of
relative:total clauses). An abnormal ratio may indicate a brain
disorder. For example, a speech pattern may include a frequency of
subordinate clauses. An increase in subordinate clauses has been
observed in the speech of psychopaths (see, e.g., Hancock et al.,
"Hungry like the wolf: A word-pattern analysis of the language of
psychopaths," Legal and Criminological Psychology, 2011; DOI:
10.1111/j.2044-8333.2011.02025.x, which is incorporated herein by
reference). For example, a speech pattern may include a relatedness
of lexical content such as semantic or sentential priming. A speech
pattern of abnormal priming may indicate a brain disorder such as
schizophrenia. For example, a speech pattern may include a
frequency of one or more use of cohesive ties, e.g., as
demonstrated by references, conjunctions, or lexical cohesion. A
low frequency of reference ties has been observed in patients
suffering from schizophrenia. For example, a speech pattern may
include an hierarchical structure within a discourse, e.g., a
systematic structure in which propositions branch out from a
central proposition. A speech pattern lacking a systematic
structure may be indicative of schizophrenia.
[0252] For example, a speech pattern including a linguistic pattern
determined at the sentential level or discourse level may include a
representation of content of thought (what the patient is talking
about). For example, a speech pattern may include a representation
of form of thought (the way ideas, sentences, and words are put
together). A speech pattern containing representations of content
or form of thought that differ from those expected (e.g., as
determined from population patterns) may indicate a psychological
disorder such as schizophrenia. Examples of representations of
content or form of thought observed in schizophrenia include
derailment, loss of goal, perseveration, and tangentiality. For
example, a speech pattern may include aspects of linguistic
pragmatics (e.g., cohesion or coherence). Abnormal patterns in
pragmatics may be indicative of a brain disorder such as
schizophrenia or mania. Examples of speech patterns and content of
thought are discussed by Covington, et al., idem, and by Kuperberg
and Caplan idem. A program for classifying parts of speech (e.g.,
noun, verb, adjective, etc.) based on the surrounding context and
analysis of semantic content has been developed and is available
under the Wmatrix interface (http://ucrel.lancs.ac.uk/wmatrix/) and
has been used to analyze the speech of psychopaths (see Hancock,
idem).
[0253] In an embodiment, a speech pattern includes an acoustic
quality. In an embodiment a speech pattern includes volume. For
example, excessive or reduced volume may be indicative of a symptom
of a brain disorder. In an embodiment a speech pattern includes
prosody (the rhythm, stress, and intonation of speech). For
example, aprosody or flattened intonation can be indicative of
schizophrenia. In an embodiment, a speech pattern includes a voice
quality of phonation. In an embodiment, a speech pattern includes
pitch or timbre. For example, abnormalities in pitch have been
observed in schizophrenics. For example, a strained quality,
choking voice, or creaking voice (laryngealisation) may be
indicative of a psychological disorder. Voice qualities and volume
in linguistics are discussed by Covington, idem.
[0254] For example, the at least one speech pattern may be
represented in activity data 5132 in numerical or categorical form.
For example, a speech pattern represented in numerical form may
include one or more numerical values representing one or more
speech parameters. Particular speech parameters represented in a
speech pattern may be selected for the purpose of
evaluating/monitoring particular brain-related disorders. For
example, in an aspect a speech pattern for evaluating/monitoring
depression includes values representing the following parameters:
speech volume, frequency of word production, frequency of pauses,
and frequency of negative value words. In another aspect, a speech
pattern for evaluating/monitoring schizophrenia includes values
representing frequency of word production, frequency of pauses,
frequency of disfluencies, type:token ratio, and speech volume. A
speech parameter or pattern may be represented in activity data
5132 in categorical form; for example, frequency of word production
may be categorized as low, medium, or high rather than represented
by a specific numerical value.
[0255] In an aspect, signal processing circuitry 5124 includes a
comparator 5129 for comparing speech patterns or parameters of
patient 102 with characteristic speech patterns or parameters, in
an approach similar to that described above in connection with
comparator 254 in FIG. 2, to determine whether the patient has
complied with the prescribed treatment regimen. In an aspect,
comparator 5129 is configured to compare at least one speech
pattern of the patient with a plurality of characteristic speech
patterns. In an aspect, the result of such a comparison is either
"patient has complied" or "patient has not complied." In an aspect,
signal processing circuitry 5124 is configured to determine that
patient 102 has failed to comply with the prescribed treatment
regimen. In an aspect, signal processing circuitry 5124 is
configured to determine that patient 102 has complied with
prescribed treatment regimen 104. Determination of compliance may
be accomplished by a thresholding, windowing, or distance
computation of one or multiple parameters relative to
characteristic threshold or range values for the parameter, and
combining results for the multiple parameters. For example, for a
given parameter (relating to activity sensed with one or more
activity sensor or audio sensor), a patient parameter value higher
than a characteristic threshold value may indicate compliance of
the patient with the prescribed treatment regimen, while a patient
parameter value equal to or lower than the threshold value may
indicate non-compliance. As another example, a patient parameter
value that lies within a range of characteristic values for the
parameter may indicate compliance, while a patient parameter value
outside the range of characteristic values indicates
non-compliance. Comparator 5129 may utilize various types of
distance computations to determine whether patient parameter values
are within a threshold distance or distance range from
characteristic values. Distance computations based on one or more
parameters or data values are known (including, but not limited to,
least-squares calculations). Different activity parameters or audio
signal parameters may be given different weights depending on how
strongly indicative the parameter is of the patient compliance. In
an aspect, signal processing circuitry 5124 is configured to
determine whether the patient has complied with the prescribed
treatment regimen based upon a determination of whether the speech
corresponds to at least one of a plurality of characteristic speech
patterns. For example, the plurality of characteristic speech
patterns can include multiple characteristic speech patterns, each
corresponding to a patient speech pattern obtained at a different
treatment regimen, for example, different doses of a drug. By
identifying which characteristic speech pattern the patient speech
pattern matches or is closest to, the drug dose taken by the
patient can be determined. For example, the patient may have taken
the drug, but at a lesser dose or less often than was prescribed.
Accordingly, the patient's speech pattern matches the
characteristic speech pattern associated with the lesser dose of
drug, indicating partial, but not full, compliance of the patient
with the prescribed treatment regimen.
[0256] In an aspect, speech processor 5128 is configured to process
at least one audio signal 5112 to determine at least one speech
parameter indicative of whether the patient has complied with the
prescribed treatment regimen. Speech parameters include, but are
not limited to, measures of prosody, rhythm, stress, intonation,
variance, intensity/volume, pitch, length of phonemic syllabic
segments, and length of rising segments, for example. In an aspect,
audio data includes at least one speech parameter, which may
include, for example, one or more of prosody, rhythm, stress,
intonation, variance, intensity/volume, pitch, length of phonemic
syllabic segments, and length of rising segments. In an aspect,
signal processing circuitry 5124 includes comparator 5129 for
comparing at least one speech parameter of the patient with at
least one characteristic speech parameter to determine whether the
patient has complied with the prescribed treatment regimen. In an
aspect, comparator 5129 is configured to compare at least one
speech parameter of the patient with a plurality of characteristic
speech parameters to determine whether the patient has complied
with the prescribed treatment regimen. For example, in an aspect,
the result of such a comparison is either "patient has complied" or
"patient has not complied." In an aspect, comparator 5129
determines a level of compliance of the patient with the prescribed
treatment regimen. Determination of compliance, non-compliance, or
level of compliance may be performed with comparator 5129 using
thresholding, windowing, or distance measurements, for example, as
described herein above. Similarly, determination of compliance or
non-compliance of patient 102 with a prescribed treatment regimen
may be accomplished with the use of comparator 5129 using
approaches as described herein above.
[0257] In an aspect, activity signal 5126 includes a signal from
one or more additional activity sensor(s) 5131. In various aspects,
first activity sensor 5120 and any additional activity sensor(s)
5131 include any of the various types of activity sensor 116
described herein above, e.g., as in connection with FIG. 3. In an
aspect, signal processing circuitry 5124 processes at least one
first activity signal 5122 and at least one second activity signal
5126 using signal processing approaches as described herein above
(e.g., as described in connection with activity detection circuitry
122/activity analysis circuitry 126 in FIG. 1), to generate
activity data 5132, which is included in activity data signal 5130.
In some aspects, more than one activity data signal is generated
(e.g., activity data signal 5130 and activity signal 5140). In some
aspects, activity data from different activity sensors is
transmitted in separate activity data signals. In other aspects,
activity data from multiple activity sensors is transmitted in a
single activity data signal. In an aspect, audio data signal 5136
is a radio frequency signal containing telecommunication data. In
some aspects, audio data signal 5136 is combined with activity data
signal 5130. In some aspects, communication system 5102 includes
patient identification circuitry 5142, which is used to determine
the presence of patient 102 based on identity signal 5144, using an
approach as described herein above, e.g., in connection with
patient identification circuitry 222 in FIG. 2. In some aspects,
communication system 5102 includes notification circuitry 5146,
which functions in the same manner as notification circuitry 290 in
FIG. 2. In an aspect, communication system 5102 includes threat
detection circuitry 5148 in signal processing circuitry 5124.
Threat detection circuitry 5148 is used for determining, based upon
at least one of the at least one first activity signal and the at
least one second activity signal, whether the patient poses a
threat. Threat can be determined using approaches as described, for
example, in U.S. Patent Application 2006/0190419 dated Aug. 24,
2016 to Bunn et al., and U.S. Patent Application 2006/00208556
dated Feb. 9, 2006 to Bunn et al., both of which are incorporated
herein by reference. If it is determined that that patient poses a
threat, a notification indicative of the threat is generated with
notification circuitry 5146, and the notification is delivered to
the threatened party via warning circuitry 5166 in monitoring
system 5106. Alternatively, or in addition, warning circuitry may
be located separately from monitoring system 5106. Signal
processing circuitry 5124, patient identification circuitry 5142,
notification circuitry 5146, threat detection circuitry 5148, and
transmitting device 5134 are components of control/processing
circuitry 5150.
[0258] Monitoring system 5106 includes at least one receiving
device 5138 for use at a monitoring location 5108 for receiving at
least one activity data signal 5130 and at least one audio data
signal 5136 (and, optionally one or more additional activity data
signal 5140) from communication system 5102 and is similar to
receiving device 136 in FIGS. 1 and 4. Audio data signal 5136
includes audio data 5151 representing speech from patient 102
sensed with at least one audio sensor 5110 at the patient location
5104 during use of communication system 5102, and transmitted to
the monitoring location 5108. Activity data signal 5130 includes
activity data 5132 indicative of whether patient 102 has complied
with the prescribed treatment regimen 104. Activity data 5132
represents at least one first activity of the patient. Monitoring
system 5106 includes signal processing circuitry 5152, which is
configured to process the at least one activity data signal 5130 to
determine, based upon the at least one first activity of the
patient and at least one second activity of the patient, whether
the patient has complied with the prescribed treatment regimen, and
reporting circuitry 5154 configured to report a conclusion based on
the determination of whether the patient has complied with the
prescribed treatment regimen. Signal processing circuitry 5152 is
substantially similar to signal processing circuitry 150 as
discussed in connection with FIGS. 1 and 4. Reporting circuitry
5154 is substantially the same as reporting circuitry 160 as
discussed in connection with FIGS. 1 and 4. Signal processing
circuitry 5152 and reporting circuitry 5154 are components of
control/processing circuitry 5156 in monitoring system 5106. In an
aspect, control/processing circuitry 5156 includes compliance
determination circuitry 5160, which functions in the same manner as
compliance determination circuitry 156 in FIGS. 1 and 4, as
discussed herein above. In an aspect control/processing circuitry
5156 includes patient identification circuitry 5162, which
determines a presence of patient 102 at patient location 5104 based
on identity signal 5164, in the same manner as patient
identification circuitry 410 depicted in FIG. 4 and described
herein above. In an aspect, control/processing circuitry 5156
includes warning circuitry 5166, which delivers a warning to a
threatened party in response to a notification. The notification is
received from the patient location, e.g., in the form of
notification signal 5168 from transmitting device 5134, as
described herein above. Delivering a warning to a threatened party
may include, for example, displaying a warning message, playing a
recorded warning message, or generating an audible alarm tone. The
warning may be delivered in the same general manner as conclusion
162 is reported by reporting circuitry 160, as described herein
above, in connection with FIG. 4.
[0259] FIG. 52 is a flow diagram of a method 5200 relating to
monitoring compliance of a patient with a prescribed treatment
regimen using a system such as system 5102 in FIG. 51 according to
principles as described herein above. Method 5200 includes sensing
with at least one audio sensor in a communication system at least
one audio signal including patient speech from a patient at a
patient location during use of the communication system, the
patient having a brain-related disorder and a prescribed treatment
regimen for treating at least one aspect of the brain-related
disorder, as indicated at 5202; sensing with at least one first
activity sensor in the communication system at least one first
activity signal indicative of a first activity of the patient, as
indicated at 5204; processing with signal processing circuitry the
at least one first activity signal and at least one second activity
signal indicative of a second activity of the patient to generate
at least one activity data signal, the activity data signal
containing data indicative of whether the patient has complied with
the treatment regimen, as indicated at 5206; and transmitting the
at least one activity data signal and at least one audio data
signal based on the at least one audio signal to a receiving device
at a monitoring location with a transmitting device at the patient
location, as indicated at 5208.
[0260] FIG. 53 is a block diagram of a computer program product
5300 for implementing a method 5200 as described in connection with
FIG. 52. Computer program product 5300 includes a signal-bearing
medium 5302 bearing one or more instructions for controlling
sensing of at least one audio signal including patient speech from
a patient at a patient location, the patient having a brain-related
disorder and a prescribed treatment regimen for treating at least
one aspect of the brain-related disorder; one or more instructions
for controlling sensing with at least one first activity sensor in
an unobtrusive activity-detection system of at least one first
activity signal indicative of a first activity of the patient; one
or more instructions for processing with signal processing
circuitry the at least one first activity signal and at least one
second activity signal indicative of a second activity of the
patient to generate at least one activity data signal, the activity
data signal containing data indicative of whether the patient has
complied with the treatment regimen; and one or more instructions
for controlling transmitting with a transmitting device at the
patient location of the at least one activity data signal and at
least one audio data signal based on the at least one audio signal
to a receiving device at a monitoring location, as indicated at
5304. Signal-bearing medium 5302 may be, for example, a
computer-readable medium 5306, a recordable medium 5308, a
non-transitory signal-bearing medium 5310, or a communications
medium 5312, examples of which are described herein above.
[0261] FIG. 54 is a block diagram of a system 5400 for implementing
a method as described in connection with FIG. 52. System 5400
includes a computing device 5402 and instructions that when
executed on the computing device cause the computing device to
control sensing with at least one audio sensor of at least one
audio signal including patient speech from a patient at a patient
location, the patient having a brain-related disorder and a
prescribed treatment regimen for treating at least one aspect of
the brain-related disorder; control sensing with at least one first
activity sensor in an unobtrusive activity-detection system of at
least one first activity signal indicative of a first activity of
the patient; process with signal processing circuitry the at least
one first activity signal and at least one second activity signal
indicative of a second activity of the patient to generate at least
one activity data signal, the activity data signal containing data
indicative of whether the patient has complied with the treatment
regimen; and control transmitting with a transmitting device at the
patient location of the at least one activity data signal and at
least one audio data signal based on the at least one audio signal
to a receiving device at a monitoring location, as indicated at
5404. System 5400 may be, for example, a cell phone configured with
application software 5406, a computing system or device 5408, or a
microprocessor-based system 5410.
[0262] FIG. 55 is a flow diagram of a method 5500 of monitoring
compliance of a patient with a treatment regimen, using a system
such as monitoring system 5106 in FIG. 51. In an aspect, method
5500 includes receiving at least one audio data signal with a
receiving device at a monitoring location, the audio data signal
including audio data representing speech sensed from a patient at a
patient location during use of a communication system, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder, as
indicated at 5502; receiving at least one activity data signal with
the receiving device, the activity data signal including activity
data indicative of whether the patient has complied with the
treatment regimen, the activity data representing at least one
first activity of the patient, as indicated at 5504; determining
with signal processing circuitry at the monitoring location whether
the patient has complied with the treatment regimen, based upon the
at least one first activity of the patient and upon at least one
second activity of the patient, as indicated at 5506; and reporting
with reporting circuitry a conclusion based on the determination of
whether the patient has complied with the prescribed treatment
regimen, as indicated at 5508.
[0263] FIG. 56 is a block diagram of a computer program product
5600 for implementing a method 5500 as described in connection with
FIG. 55. Computer program product 5600 includes a signal-bearing
medium 5602 bearing one or more instructions for controlling the
receiving of at least one audio data signal with a receiving device
at a monitoring location, the audio data signal including audio
data representing speech sensed from a patient at a patient
location during use of a communication system, the patient having a
brain-related disorder and a prescribed treatment regimen for
treating at least one aspect of the brain-related disorder; one or
more instructions for controlling the receiving of at least one
activity data signal with the receiving device, the activity data
signal including activity data indicative of whether the patient
has complied with the treatment regimen, the activity data
representing at least one first activity of the patient; one or
more instructions for determining whether the patient has complied
with the treatment regimen, based upon the at least one first
activity of the patient and upon at least one second activity of
the patient; and one or more instructions for controlling reporting
circuitry to report a conclusion based on the determination of
whether the patient has complied with the prescribed treatment
regimen, as indicated at 5604. Signal-bearing medium 5602 may be,
for example, a computer-readable medium 5606, a recordable medium
5608, a non-transitory signal-bearing medium 5610, or a
communications medium 5612, examples of which are described herein
above.
[0264] FIG. 57 is a block diagram of a system 5700 for implementing
a method as described in connection with FIG. 52. System 5700
includes a computing device 5702 and instructions that when
executed on the computing device cause the computing device to
control the receiving of at least one audio data signal with a
receiving device at a monitoring location, the audio data signal
including audio data representing speech sensed from a patient at a
patient location during use of a communication system, the patient
having a brain-related disorder and a prescribed treatment regimen
for treating at least one aspect of the brain-related disorder;
control the receiving of at least one activity data signal with the
receiving device, the activity data signal including activity data
indicative of whether the patient has complied with the treatment
regimen, the activity data representing at least one first activity
of the patient; determine whether the patient has complied with the
treatment regimen, based upon the at least one first activity of
the patient and upon at least one second activity of the patient;
and control reporting circuitry to report a conclusion based on the
determination of whether the patient has complied with the
prescribed treatment regimen, as indicated at 5704. System 5700 may
be, for example, a cell phone configured with application software
5706, a computing system or device 5708, or a microprocessor-based
system 5710.
[0265] The herein described subject matter sometimes illustrates
different components contained within, or connected with, different
other components. It is to be understood that such depicted
architectures are merely exemplary, and that in fact many other
architectures may be implemented which achieve the same
functionality. In a conceptual sense, any arrangement of components
to achieve the same functionality is effectively "associated" such
that the desired functionality is achieved. Hence, any two
components herein combined to achieve a particular functionality
can be seen as "associated with" each other such that the desired
functionality is achieved, irrespective of architectures or
intermedial components. Likewise, any two components so associated
can also be viewed as being "operably connected", or "operably
coupled," to each other to achieve the desired functionality, and
any two components capable of being so associated can also be
viewed as being "operably couplable," to each other to achieve the
desired functionality. Specific examples of operably couplable
include but are not limited to physically mateable and/or
physically interacting components, and/or wirelessly interactable,
and/or wirelessly interacting components, and/or logically
interacting, and/or logically interactable components.
[0266] In some instances, one or more components may be referred to
herein as "configured to," "configured by," "configurable to,"
"operable/operative to," "adapted/adaptable," "able to,"
"conformable/conformed to," etc. Those skilled in the art will
recognize that such terms (e.g., "configured to") generally
encompass active-state components and/or inactive-state components
and/or standby-state components, unless context requires
otherwise.
[0267] While particular aspects of the present subject matter
described herein have been shown and described, it will be apparent
to those skilled in the art that, based upon the teachings herein,
changes and modifications may be made without departing from the
subject matter described herein and its broader aspects and,
therefore, the appended claims are to encompass within their scope
all such changes and modifications as are within the true spirit
and scope of the subject matter described herein. It will be
understood by those within the art that, in general, terms used
herein, and especially in the appended claims (e.g., bodies of the
appended claims) are generally intended as "open" terms (e.g., the
term "including" should be interpreted as "including but not
limited to," the term "having" should be interpreted as "having at
least," the term "includes" should be interpreted as "includes but
is not limited to," etc.). It will be further understood by those
within the art that if a specific number of an introduced claim
recitation is intended, such an intent will be explicitly recited
in the claim, and in the absence of such recitation no such intent
is present. For example, as an aid to understanding, the following
appended claims may contain usage of the introductory phrases "at
least one" and "one or more" to introduce claim recitations.
However, the use of such phrases should not be construed to imply
that the introduction of a claim recitation by the indefinite
articles "a" or "an" limits any particular claim containing such
introduced claim recitation to claims containing only one such
recitation, even when the same claim includes the introductory
phrases "one or more" or "at least one" and indefinite articles
such as "a" or "an" (e.g., "a" and/or "an" should typically be
interpreted to mean "at least one" or "one or more"); the same
holds true for the use of definite articles used to introduce claim
recitations. In addition, even if a specific number of an
introduced claim recitation is explicitly recited, those skilled in
the art will recognize that such recitation should typically be
interpreted to mean at least the recited number (e.g., the bare
recitation of "two recitations," without other modifiers, typically
means at least two recitations, or two or more recitations).
Furthermore, in those instances where a convention analogous to "at
least one of A, B, and C, etc." is used, in general such a
construction is intended in the sense one having skill in the art
would understand the convention (e.g., "a system having at least
one of A, B, and C" would include but not be limited to systems
that have A alone, B alone, C alone, A and B together, A and C
together, B and C together, and/or A, B, and C together, etc.). In
those instances where a convention analogous to "at least one of A,
B, or C, etc." is used, in general such a construction is intended
in the sense one having skill in the art would understand the
convention (e.g., "a system having at least one of A, B, or C"
would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C
together, and/or A, B, and C together, etc.). It will be further
understood by those within the art that typically a disjunctive
word and/or phrase presenting two or more alternative terms,
whether in the description, claims, or drawings, should be
understood to contemplate the possibilities of including one of the
terms, either of the terms, or both terms unless context dictates
otherwise. For example, the phrase "A or B" will be typically
understood to include the possibilities of "A" or "B" or "A and
B."
[0268] With respect to the appended claims, those skilled in the
art will appreciate that recited operations therein may generally
be performed in any order. Also, although various operational flows
are presented in a sequence(s), it should be understood that the
various operations may be performed in other orders than those
which are illustrated, or may be performed concurrently. Examples
of such alternate orderings may include overlapping, interleaved,
interrupted, reordered, incremental, preparatory, supplemental,
simultaneous, reverse, or other variant orderings, unless context
dictates otherwise. Furthermore, terms like "responsive to,"
"related to," or other past-tense adjectives are generally not
intended to exclude such variants, unless context dictates
otherwise.
[0269] While various aspects and embodiments have been disclosed
herein, other aspects and embodiments will be apparent to those
skilled in the art. The various aspects and embodiments disclosed
herein are for purposes of illustration and are not intended to be
limiting, with the true scope and spirit being indicated by the
following claims.
* * * * *
References